Bagos PG, Nikolopoulos GK. Generalized least squares for assessing trends in cumulative meta-analysis with applications in genetic epidemiology. 2009, Journal of Clinical Epidemiology, 62 (10): 1037-1044 (Impact Factor:  2.956, citations: 1)

1.       Kulinskaya, E. and Koricheva, J. (2010), Use of quality control charts for detection of outliers and temporal trends in cumulative meta-analysis. Research Synthesis Methods, 1: n/a. doi: 10.1002/jrsm.29

Bagos PG, Nikolopoulos GK. Mixed-effects Poisson regression models for meta-analysis of follow-up studies with constant or varying durations. 2009, The International Journal of Biostatistics, 5(1), Article 21. (Impact Factor:  -, citations: 1)

2.       James J. Sejvar, Andrew L. Baughman, Matthew Wise, Oliver W. Morgan. Population Incidence of Guillain-Barré Syndrome: A Systematic Review and Meta-Analysis. Neuroepidemiology 2011;36:123-133

Dimou NL, Nikolopoulos GK, Hamodrakas SJ, Bagos PG. Fcgamma receptor polymorphisms and their association with periodontal disease: A meta-analysis. 2010 Journal of Clinical Periodontology, 37(3):255-65 (Impact Factor: 3.549, citations: 3)

3.       Yokoyama T, Kobayashi T, Yamamoto K, Yamagata A, Oofusa K, Yoshie H. Proteomic profiling of human neutrophils in relation to immunoglobulin G Fc receptor IIIb polymorphism. J Periodontal Res. 2010 Jul 6. [Epub ahead of print]

4.       Zhuang Y, Xu W, Shen Y, Li J. Fcγ receptor polymorphisms and clinical efficacy of rituximab in non-Hodgkin lymphoma and chronic lymphocytic leukemia. Clin Lymphoma Myeloma Leuk. 2010 Oct;10(5):347-52

5.       Deng H, Liu F, Pan Y, Jin X, Wang H, Cao J. BsmI, TaqI, ApaI, and FokI polymorphisms in the vitamin D receptor gene and periodontitis: a meta-analysis of 15 studies including 1338 cases and 1302 controls. J Clin Periodontol. 2011 Mar;38(3):199-207. doi: 10.1111/j.1600-051X.2010.01685.x. Epub 2010 Dec 27.

Ioannidis A, Ikonomi E, Dimou NL, Douma L, Bagos PG. Polymorphisms of Insulin Receptor (INSR) and Insulin Receptor Substrate-1 (IRS-1) genes and their association with Polycystic Ovary Syndrome: a mendelian randomization meta-analysis. 2010, Molecular Genetics and Metabolism, 99(2):174–183 (Impact Factor:  2.897, citations: 5)

6.       Mukherjee, S., Maitra, A. Molecular & genetic factors contributing to insulin resistance in polycystic ovary syndrome 2010. Indian Journal of Medical Research 131 (6), pp. 743-760             

7.       Whitaker KN: Polycystic Ovary Syndrome: An Overview. Journal of Pharmacy Practice .  2010

8.       Baranova A, Tran TP, Birerdinc A, Younossi ZM: Systematic review: association of polycystic ovary syndrome with metabolic syndrome and non-alcoholic fatty liver disease. Alimentary Pharmacology & Therapeutics 2011  

9.       Goodarzi MO, Louwers YV, Taylor KD, Jones MR, Cui J, Kwon S, Chen YD, Guo X, Stolk L, Uitterlinden AG, Laven JS, Azziz R. Replication of association of a novel insulin receptor gene polymorphism with polycystic ovary syndrome. Fertil Steril. 2011 Apr;95(5):1736-1741.e11.

10.   Baranova A, Tran TP, Birerdinc A, Younossi ZM. Systematic review: association of polycystic ovary syndrome with metabolic syndrome and non-alcoholic fatty liver disease.Aliment Pharmacol Ther. 2011 Apr;33(7):801-14. doi: 10.1111/j.1365-2036.2011.04579.x. Epub 2011 Jan 20.

Bonovas S, Nikolopoulos GK, Filioussi K, Peponi E, Bagos PG, Sitaras NM. Can statin therapy reduce the risk of melanoma? A meta-analysis of randomized controlled trials. European Journal of Epidemiology, 2010;25(1):29-35 (Impact Factor:  3.718, citations: 3)

11.   Hippisley-Cox, J., Coupland, C. Unintended effects of statins in men and women in England and Wales: Population based cohort study using the QResearch database .BMJ 340 (7758), pp. 1232

12.   Julia Hippisley-Cox, Unintended effects of statins in men and women in England and Wales: population based cohort study using the QResearch database. BMJ. 2010; 340: c2197

13.   Thomas MALFAIT. RhoC in melanoma: possible target for statin treatment. MSc Thesis, 2010, Universiteit Gent

Bagos PG, Tsirigos KD, Liakopoulos TD, Hamodrakas SJ. Prediction of lipoprotein signal peptides in Gram-positive bacteria with Hidden Markov Models, 2008, J Proteome Research, 7(12):5082-93. (Impact Factor: 5.684, citations: 4)

14.   Giombini E, Orsini M, Carrabino D, Tramontano A An automatic method for identifying surface proteins in bacteria: SLEP BMC Bioinformatics 2010, 11:39

15.   Goudenège, D., Avner, S., Lucchetti-Miganeh, C., Barloy-Hubler, F. CoBaltDB: Complete bacterial and archaeal orfeomes subcellular localization database and associated resources. 2010 BMC Microbiology 10, art. no. 88

16.   Thompson BJ, Widdick DA, Hicks MG, Chandra G, Sutcliffe IC, Palmer T, Hutchings MI.  Investigating lipoprotein biogenesis and function in the model Gram-positive bacterium Streptomyces coelicolor. Mol Microbiol. 2010 Jun 21. [Epub ahead of print]

17.   Stefanie Storf, Friedhelm Pfeiffer, Kieran Dilks, Zhong Qiang Chen, Saheed Imam, and Mechthild Pohlschröder. Mutational and Bioinformatic Analysis of  Haloarchaeal Lipobox-Containing Proteins. Archaea Volume 2010 (2010), Article ID 410975, 11 pages doi:10.1155/2010/410975

Bagos PG, Tsirigos KD, Plessas SK, Liakopoulos TD, Hamodrakas SJ. Prediction of signal peptides in Archaea, Protein Engineering Design and Selection, 2009, 22(1): 27-35 (Impact Factor:  2.787, citations: 12)

18.   Ng, S.Y.M., VanDyke, D.J., Chaban, B., Wu, J., Nosaka, Y., Aizawa, S.-I., Jarrell, K.F. Different minimal signal peptide lengths recognized by the archaeal prepilin-like peptidases FlaK and PibD 2009 Journal of Bacteriology 191 (21), pp. 6732-6740

19.   Choo KH, Tan TW, Ranganathan S. A comprehensive assessment of N-terminal signal peptides prediction methods. BMC Bioinformatics 2009, 10(Suppl 15):S2

20.   Ellen, A.F., Albers, S.-V., Driessen, A.J.M. Comparative study of the extracellular proteome of Sulfolobus species reveals limited secretion 2009 Extremophiles 14 (1), pp. 87-98

21.   Magidovich H, Yurist-Doutsch S, Konrad Z, Ventura VV, Dell A, Hitchen PG, Eichler J. AglP is a S-adenosyl-L-methionine-dependent methyltransferase that participates in the N-glycosylation pathway of Haloferax volcanii. Mol Microbiol. 2010

22.   KS Auernik  , RM Kelly. Impact of Molecular Hydrogen on Chalcopyrite Bioleaching by the Extremely Thermoacidophilic Archaeon Metallosphaera sedula. Appl. Environ. Microbiol. 2010, doi:10.1128/AEM.02016-09

23.   Goudenège, D., Avner, S., Lucchetti-Miganeh, C., Barloy-Hubler, F. CoBaltDB: Complete bacterial and archaeal orfeomes subcellular localization database and associated resources. 2010 BMC Microbiology 10, art. no. 88

24.   Albert F. Ellen, Behnam Zolghadr, Arnold J M Driessen, and Sonja Verena Albers Shaping the archaeal cell envelope. Archaea, 2010, in press

25.   Quax, T.E.F., KrupoviČ, M., Lucas, S., Forterre, P., Prangishvili, D. The Sulfolobus rod-shaped virus 2 encodes a prominent structural component of the unique virion release system in Archaea 2010 Virology 404 (1), pp. 1-4

26.   Łabaj, P.P., Leparc, G.G., Bardet, A.F., Kreil, G., Kreil, D.P.  Single amino acid repeats in signal peptides 2010 , FEBS Journal 277 (15), pp. 3147-3157

27.   Du X, Zhang SW. Prediction of signal peptide cleavage sites with template matching fusion algorithm. Signal Processing (ICSP), 2010 IEEE 10th International Conference on Date:24-28 Oct. 2010 pp 1801 – 1804

28.   Ting-ting Liu  Proteomic analysis of the exoproteome of the thermophilic archaeon Sulfolobus acidocaldarius DSM 639. Graduate Institute of Systems Biology and Bioinformatics. MSc Thesis, 2009

29.   Petra Worm, Alfons J. M. Stams, Xu Cheng and Caroline M. Plugge. Growth- and substrate-dependent transcription of formate dehydrogenase and hydrogenase coding genes in Syntrophobacter fumaroxidans and Methanospirillum hungatei. Microbiology 157 (2011), 280-289 ; DOI  10.1099/mic.0.043927-0

Bagos PG. Plasminogen Activator Inhibitor-1 4G/5G and 5,10-methylene-tetrahydrofolate reductase C677T polymorphisms in Polycystic Ovary Syndrome. 2009, Molecular Human Reproduction, 15(1):19-26 (Impact Factor:  2.537, citations: 1)

30.   Bohler H Jr, Mokshagundam S, Winters SJ. Adipose tissue and reproduction in women. Fertil Steril. 2009

Bagos PG. A unification of multivariate methods for meta-analysis of genetic association studies. Statistical Applications in Genetics and Molecular Biology, 2008, 7(1), Article 13 (Impact Factor:  1.773, citations: 4)

31.   Li H, Ha TC, Tai BC. XRCC1 gene polymorphisms and breast cancer risk in different populations: a meta-analysis. Breast. 2009; 18(3):183-91.

32.   Andreas Ziegler, Inke R. König, Friedrich Pahlke. A Statistical Approach to Genetic Epidemiology: Concepts and Applications.Wiley-Blackwell, 2010

33.   Pereira TV, Patsopoulos NA, Pereira AC, Krieger JE. Strategies for genetic model specification in the screening of genome-wide meta-analysis signals for further replication. International Journal of Epidemiology, 2010

34.   Madden LV, Paul PA: Meta-Analysis for Evidence Synthesis in Plant Pathology: An Overview. Phytopathology 2011, 101:16-30.  

Litou ZI, Bagos PG, Tsirigos KD, Liakopoulos TD, Hamodrakas SJ. Prediction of Cell Wall sorting signals in Gram-positive bacteria with a Hidden Markov Model: application to complete genomes.  Journal of Bioinformatics and Computational Biology, 2008 6(2):387-401. (Impact Factor:-, citations:1)

35.   Mariscotti JF, García-del Portillo F, Pucciarelli MG. The Listeria monocytogenes sortase-B recognizes varied amino acids at position 2 of the sorting motif. J Biol Chem. 2009; 284(10):6140-6.

36.   Goudenège, D., Avner, S., Lucchetti-Miganeh, C., Barloy-Hubler, F. CoBaltDB: Complete bacterial and archaeal orfeomes subcellular localization database and associated resources. 2010 BMC Microbiology 10, art. no. 88

Theodoropoulou MC, Bagos PG, Spyropoulos IC, Hamodrakas SJ. gpDB: a database of G-proteins, GPCRs, Effectors and their interactions. Bioinformatics. 2008, 24(12):1471-2. (Impact Factor: 4.328, citations: 7)

37.   Harmar AJ, Hills RA, Rosser EM, Jones M, Buneman OP, Dunbar DR, Greenhill SD, Hale VA, Sharman JL, Bonner TI, Catterall WA, Davenport AP, Delagrange P, Dollery CT, Foord SM, Gutman GA, Laudet V, Neubig RR, Ohlstein EH, Olsen RW, Peters J, Pin JP, Ruffolo RR, Searls DB, Wright MW, Spedding M. IUPHAR-DB: the IUPHAR database of G protein-coupled receptors and ion channels. Nucleic Acids Res. 2009 Jan;37(Database issue):D680-5.

38.   R. Prasobh and Narayanan Manoj. The Repertoire of Heterotrimeric G Proteins and RGS Proteins in Ciona intestinalis. PLoS One. 2009; 4(10): e7349.

39.   Lisa M Simpson, Bruck Taddese, Ian D Wall and Christopher A Reynolds. Bioinformatics and molecular modelling approaches to GPCR oligomerization. Current Opinion in Pharmacology Volume 10, Issue 1, February 2010, Pages 30-37

40.   Khelashvili G, Dorff K, Shan J, Camacho-Artacho M, Skrabanek L, Vroling B, Bouvier M, Devi LA, George SR, Javitch JA, Lohse MJ, Milligan G, Neubig RR, Palczewski K, Parmentier M, Pin JP, Vriend G, Campagne F, Filizola M. GPCR-OKB: the G Protein Coupled Receptor Oligomer Knowledge Base. Bioinformatics. 2010 Jul 15;26(14):1804-5

41.   Chen XP, Yang W, Fan Y, Luo JS, Hong K, Wang Z, Yan JF, Chen X, Lu JX, Benovic JL, Zhou NM. Structural determinants in the second intracellular loop of the human cannabinoid CB(1) receptor mediate selective coupling to G(s) and G(i). Br J Pharmacol. 2010 Aug 23. [Epub ahead of print]

42.   Yukimitsu Yabuki, Masami Ikeda, Yuri Mukai-Ikeda and Yoshihisa Ishida. Development of Prediction Method for GPCRG-protein Coupling Selectivity Using Amino Acid Properties. The Open Structural Biology Journal, 2009, 3, 149-158

43.   XP Chen, W Yang, Y Fan, JS Luo, K Hong, Z Wang, JF Yan, X Chen, JX Lu, JL Benovic, M Zhou Structural determinants in the second intracellular loop of the human cannabinoid CB1 receptor mediate selective coupling to Gs and Gi British Journal of Pharmacology Volume 161, Issue 8, pages 1817–1834, December 2010

Nikolopoulos GK, Dimou NL, Hamodrakas SJ, Bagos PG. Cytokine gene polymorphisms in periodontal disease: A meta-analysis of 53 studies including 4178 cases and 4590 controls. Journal of Clinical Periodontology, 2008,35(9):754-67 (Impact Factor: 3.193, citations: 19)

44.   Noack B, Görgens H, Lorenz K, Ziegler A, Hoffmann T, Schackert HK. TLR4 and IL-18 gene variants in aggressive periodontitis. J Clin Periodontol. 2008;35(12):1020-6

45.   Néstor J. López, Carlos Y. Valenzuela, and Lilian Jara. Interleukin-1 Gene Cluster Polymorphisms Associated with Periodontal Disease in Type 2 Diabetes. Journal of Periodontology, Posted online on July 7, 2009

46.   Shao MY, Huang P, Cheng R, Hu T. Interleukin-6 polymorphisms modify the risk of periodontitis: a systematic review and meta-analysis. J Zhejiang Univ Sci B. 2009;10(12):920-7.

47.   Raunio T. GENE POLYMORPHISM AND SYSTEMIC INFLAMMATORY RESPONSE IN CHRONIC PERIODONTITIS. Ph.D. Thesis. 2009, FACULTY OF MEDICINE, INSTITUTE OF DENTISTRY, DEPARTMENT OF PERIODONTOLOGY AND GERIATRIC DENTISTRY, INSTITUTE OF DIAGNOSTICS, DEPARTMENT OF MEDICAL MICROBIOLOGY,UNIVERSITY OF OULUISBN 978-951-42-9235-4 OULU UNIVERSITY PRESS

48.   Shaqman MH, Periodontitis, Inflammatory Markers and Solid Organ Transplant Recipients. 2009, M.Sc. Thesis, University of Connecticut

49.   Rafał Płoski, Zofia T. Bilińska. Dilated cardiomyopathy in the postgenomic era. Kardiol Pol 2009; 67: 1248-1249

50.   Manish Arora, Jennifer Weuve, Katja Fall, Nancy L. Pedersen and Lorelei A. Mucci. An Exploration of Shared Genetic Risk Factors Between Periodontal Disease and Cancers: A Prospective Co-Twin Study. American Journal of Epidemiology 2010 171(2):253-259; doi:10.1093/aje/kwp340

51.   Alexandrina L. Dumitrescu and Junya Kobayashi. Genetic Variability and Periodontal Disease. In Dumitrescu A.L. (Ed) Etiology and Pathogenesis of Periodontal Disease. Springer Berlin Heidelberg, 2009

52.   Marja L. Laine,, Bruno G. Loos, W. Crielaard. Gene polymorphisms in chronic periodontitis International Journal of Dentistry, 2009

53.   AhmadReza Ebadian, Mehrdad Radvar, HamidReza Arab Jalil TavakkolAfshari,  Naser Sargolzaei, Salman Gharegozloo, Azam Brook, Mojhgan Shirkhani. Analysis of Proinflammatory Cytokines Gene Polymorphisms in Generalized Aggressive Periodontitis (GAgP) J Mash Dent Sch 2009; 33(3): 231-40. 

54.   Stabholz A, Soskolne WA, Shapira L. Genetic and environmental risk factors for chronic periodontitis and aggressive periodontitis. Periodontol 2000. 2010;53:138-53..

55.   Cota LO, Viana MB, Moreira PR, Gomez RS, Cortelli JR, Cortelli SC, Costa FO. Gingival overgrowth in cyclosporine, tacrolimus, or sirolimus-based immunosuppressive regimens and the single nucleotide IL-6 (-174 G/C) gene polymorphism. Arch Oral Biol. 2010 Apr 27

56.   Lazenby, M.G., Crook, M.A., The innate immune system and diabetes mellitus: The relevance of periodontitis? A hypothesis 2010 , Clinical Science 119 (10), pp. 423-429

57.   Ladhani, S.N., Davila, S., Hibberd, M.L., Heath, P.T., Ramsay, M.E., Slack, M.P.E., Pollard, A.J., Booy, R., Association between single-nucleotide polymorphisms in Mal/TIRAP and interleukin-10 genes and susceptibility to invasive Haemophilus influenzae serotype b infection in immunized children 2010, Clinical Infectious Diseases 51 (7), pp. 761-767

58.   Deng H, Liu F, Pan Y, Jin X, Wang H, Cao J: BsmI, TaqI, ApaI, and FokI polymorphisms in the vitamin D receptor gene and periodontitis: a meta-analysis of 15 studies including 1338 cases and 1302 controls. Journal of Clinical Periodontology 2011, 38:199-207.  

59.   Stashenko P, Van Dyke T, Tully P, Kent R, Sonis S, Tanner AC: Inflammation and Genetic Risk Indicators for Early Periodontitis in Adults. Journal of Periodontology 2010:1-10.  

60.   Mizuno N, Niitani M, Shiba H, Iwata T, Hayashi I, Kawaguchi H, Kurihara H: Proteome analysis of proteins related to aggressive periodontitis combined with neutrophil chemotaxis dysfunction. Journal of Clinical Periodontology 2011:no-no.  

61.   Acir Jose Dirschnabel,Fabiano Alvim-Pereira,Claudia Cristina Alvim-Pereira,Jose Fabio Bernardino,Edvaldo Antonio Ribeiro Rosa,Paula Cristina Trevilatto. Analysis of the association of IL1B(C-511T) polymorphism with dental implant loss and the clusterization phenomenon. Clinical Oral Implants Research, 2011

62.   Miguel Angel MUNOZ, Rafael BAGGIO, Joao Paulo STEFFENS, Fabio Andre SANTOS, Gibson Luiz PILATTI. Genetic and immunological features of aggressive periodontitis. Rev Sul-Bras Odontol. 2010 Mar;7(1):90-4

Tsantes AE, Nikolopoulos GK, Bagos PG, Bonovas S, Kopterides P, Vaiopoulos G. The effect of the plasminogen activator inhibitor-1 4G/5G polymorphism on the thrombotic risk. Thromb Res. 2008 (Impact Factor: 2.449, citations: 12)

63.   Sanna V, Zarrilli F, Nardiello P, D'Argenio V, Rocino A, Coppola A, Di Minno G, Castaldo G. Mutational spectrum of F8 gene and prothrombotic gene variants in haemophilia A patients from Southern Italy. Haemophilia. 2008

64.   Ramón LA, Gilabert-Estellés J, Cosín R, Gilabert J, España F, Castelló R, Chirivella M, Romeu A, Estellés A. Plasminogen activator inhibitor-1 (PAI-1) 4G/5G polymorphism and endometriosis. Influence of PAI-1 polymorphism on PAI-1 antigen and mRNA expression.  Thromb Res. 2008

65.   Gialeraki, A., Politou, M., Rallidis, L., Merkouri, E., Markatos, C., Kremastinos, D., Travlou, A. Prevalence of prothrombotic polymorphisms in Greece, 2008, Genetic Testing 12 (4), pp. 541-547

66.   Marina Turello, Samantha Pasca, Roberto Daminato, Patrizia Dello Russo, Roberta Giacomello2 Ugo Venturelli and Giovanni Barillari. Retinal vein occlusion: evaluation of “classic” and “emerging” risk factors and treatment. Journal of Thrombosis and Thrombolysis. 2009. in press

67.   Kupesiz OA, Chitlur MB, Hollon W, Tosun O, Thomas R, Warrier I, Lusher JM, Rajpurkar M. Fibrinolytic parameters in children with noncatheter thrombosis: a pilot study. Blood Coagul Fibrinolysis. 2010 Jun;21(4):313-9.

68.   Zateyshchikov DA, Brovkin AN, Chistiakov DA, Nosikov VV. Advanced age, low left atrial appendage velocity, and Factor V promoter sequence variation as predictors of left atrial thrombosis in patients with nonvalvular atrial fibrillation. J Thromb Thrombolysis. 2010 Aug;30(2):192-9.

69.   Katrancioglu N, Manduz S, Ozen F, Yilmaz MB, Karahan O, Ozdemir O, Berkan O. Type I Plasminogen Activator Inhibitor 4G Allele Frequency is Associated with Chronic Venous Insufficiency. J Int Med Res. 2010 Jul-Aug;38(4):1513-8.

70.   Lenicek Krleza J, Jakovljevic G, Bronic A, Coen Herak D, Bonevski A, Stepan-Giljevic J, Roic G. Contraception-related deep venous thrombosis and pulmonary embolism in a 17-Year-old girl heterozygous for factor V leiden, prothrombin G20210A mutation, MTHFR C677T and homozygous for PAI-1 mutation: report of a family with multiple genetic risk factors and review of the literature. Pathophysiol Haemost Thromb. 2010;37(1):24-9. Epub 2010 Jul 20.

71.   Saratzis A, Abbas A, Kiskinis D, Melas N, Saratzis N, Kitas GD. Abdominal Aortic Aneurysm: A Review of the Genetic Basis. Angiology. 2010 Jun 21. [Epub ahead of print]

72.   Nurkay Katrancioğlu, Şinasi Manduz, Oğuz Karahan, Ahmet Turhan Kılıç, Öcal Berkan. The myocardial infarction in a young woman with heterozygous MTHRF and PAI-1 gene mutations. Cumhuriyet Medical Journal (CMJ), Vol 32, No 2 (2010)

73.   Zainullina A. G., Khusnutdinova E. K  The Role of fibrinolytic system genes in the development of gestosis. Molecular Medicine №5 2010

74.   Roman M. Sniecinski,, Marcie J Hursting,  Michael J. Paidas and Jerrold H. Levy, Etiology and Assessment of Hypercoagulability with Lessons from Heparin-Induced Thrombocytopenia. Anesthesia & Analgesia, January 2011 vol. 112 no. 1 46-58

Bagos PG, Elefsinioti AL, Nikolopoulos GK, Hamodrakas SJ.  The GNB3 C825T polymorphism and Essential Hypertension: a meta-analysis of 34 studies including 14094 cases and 17760 controls, 2007, Journal of Hypertension, 25(3):487-500 (Impact Factor: 5.132, citations: 22)

75.   Chunyu Zhang, Shigang Zhao, Guangming Niu, Rile Hu, Zhiguang Wang, Mingfang Jiang, Rile Hu. Genetic predisposition to essential hypertension in a Mongolian population: Detecting the C825T polymorphism of the G-protein beta 3 subunit gene. Nerve Regeneration Research，2007，2（3)：146-150

76.   Deng AY. Genetic basis of polygenic hypertension. Hum Mol Genet. 2007;16 Spec No. 2:R195-202.

77.   Lahiry P, Pollex RL, Hegele RA. Uncloaking the Genetic Determinants of Metabolic Syndrome. J Nutrigenet Nutrigenomics 2008;1:118–125

78.   Haga SB, Burke W. Pharmacogenetic testing: not as simple as it seems. Genet Med. 2008;10(6):391-5.

79.   Peters BJ, Maitland-van der Zee AH, Stricker BH, van Wieren-de Wijer DB, de Boer A, Kroon AA, de Leeuw PW, Schiffers P, Janssen RG, van Duijn CM, Klungel OH. Effectiveness of statins in the reduction of the risk of myocardial infarction is modified by the GNB3 C825T variant. Pharmacogenet Genomics. 2008;18(7):631-636.

80.   Daimon, M., Sato, H., Sasaki, S., Toriyama, S., Emi, M., Muramatsu, M., Hunt, S.C., et al. Salt consumption-dependent association of the GNB3 gene polymorphism with type 2 DM  Biochemical and Biophysical Research Communications 374 (3), pp. 576-580: 2008

81.   Welsh P, Packard CJ, Sattar N. Novel antecedent plasma biomarkers of cardiovascular disease: improved evaluation methods and comparator benchmarks raise the bar. Curr Opin Lipidol. 2008;19(6):563-71.

82.   Rosskopf D, Michel MC. Pharmacogenomics of G protein-coupled receptor ligands in cardiovascular medicine. Pharmacol Rev. 2008; 60(4):513-35   

83.   Bizios, Anna Serletis; Sheldon, Robert S.Vasovagal syncope: state or trait? Current Opinion in Cardiology. 2009, 24(1):68-73

84.   Bamidele O. Tayo; Amy Luke; Xiaofeng Zhu; Adebowale Adeyemo and Richard S. Cooper. Association of Regions on Chromosomes 6 and 7 with Blood Pressure in Nigerian Families. Circulation, 2009, in press

85.   Sun C, Wang JJ, Islam FM, Heckbert SR, Klein R, Siscovick DS, Klein BE, Wong TY.  Hypertension genes and retinal vascular calibre: the Cardiovascular Health Study. J Hum Hypertens. 2009 Jan 15. [Epub ahead of print]

86.   Minushkina LO, Brazhnik VA, Nosikov VV, Sidorenko BA, Zateĭshchikov DA Association of genetic factors with clinical peculiarities of hypertensive disease in patients with burdened familial anamnesis. Kardiologiia. 2009;49(2):38-46

87.   Dorr M, Rosskopf D, Hentschel K. beta-Blocker Therapy and Heart Rate Control During Exercise Testing in the General Population: Role of a Common G Protein beta 3 Subunit Variant BASIC & CLINICAL PHARMACOLOGY & TOXICOLOGY 104 (6): 500-500 JUN 2009

88.   Vasileios F. Panoulas;  Jacqueline P. Smith;  Antonios Stavropoulos-Kalinoglou;  Karen M. J. Douglas;  Peter Nightingale; George D. Kitas Lack of an Association of GNB3 C825T Polymorphism and Blood Pressure in Patients with Rheumatoid Arthritis Clinical and Experimental Hypertension, 1525-6006, Volume 31, Issue 5, 2009, Pages 428 – 439   

89.   Chistiakov DA, Spitsina EV, Nikitin AG, Strokov IA, Nosikov VV. A splice variant of GNB3 and peripheral polyneuropathy in type 1 diabetes. Dis Markers. 2009;26(3):111-7.

90.   Kelly, T.N., Rice, T.K., Gu, D., Hixson, J.E., Chen, J., Liu, D., Jaquish, C.E., (...), He, J. Novel genetic variants in the α-adducin and guanine nucleotide binding protein β-polypeptide 3 genes and salt sensitivity of blood pressure 2009 American Journal of Hypertension 22 (9), pp. 985-992

91.   Dai-Hai Yu, De-Pei Liu, Lai-Yuan Wang, Jing Chen, Cashell E. Jaquish, Dabeeru C. Rao, James E. Hixson, Jian-Feng Huang, Chung-Shiuan Chen, Charles Gu, Ji-Chun Chen, Jie Cao, Shu-Feng Chen, Paul K. Whelton, Jiang He, Dong-Feng Gu and GenSalt Collaborative Research Group. Genetic variants in the ADD1 and GNB3 genes and blood pressure response to potassium supplementation. Frontiers of Medicine in China. Volume 4, Number 1 / March, 2010

92.   Gómez-Gallego F, Ruiz JR, Buxens A, Altmäe S, Artieda M, Santiago C, González-Freire M, Verde Z, Arteta D, Martínez A, Tejedor D, Lao JI, Arenas J, Lucia A. Are elite endurance athletes genetically predisposed to lower disease risk? Physiol Genomics. 2010 Mar 3;41(1):82-90.

93.   Holmen OL, Romundstad S, Melien O. Association between the G protein β3 subunit C825T polymorphism and the occurrence of cardiovascular disease in hypertensives: The Nord-Trøndelag Health Study (HUNT). Am J Hypertens. 2010 Oct;23(10):1121-7.

94.   Marques FZ, Campain AE, Yang YH, Morris BJ. Meta-analysis of genome-wide gene expression differences in onset and maintenance phases of genetic hypertension. Hypertension. 2010 Aug;56(2):319-24. Epub 2010 Jun 28.

95.   Dörr M, Schmidt CO, Spielhagen T, Bornhorst A, Hentschel K, Franz C, Empen K, Kocher T, Diehl SR, Kroemer HK, Völzke H, Ewert R, Felix SB, Rosskopf D. β-blocker therapy and heart rate control during exercise testing in the general population: role of a common G-protein β-3 subunit variant. Pharmacogenomics. 2010 Sep;11(9):1209-21.

96.   Hoop, J.G., Lapid, M.I., Paulson, R.M., Roberts, L.W. Clinical and ethical considerations in pharmacogenetic testing: Views of physicians in 3 "early adopting" departments of psychiatry 2010 Journal of Clinical Psychiatry 71 (6), pp. 745-753

Tsantes AΕ, Nikolopoulos GΚ, Bagos PG, Tsiara C, Travlou A, Vaiopoulos G. Plasminogen Activator Inhibitor-1 4G/5G Polymorphism and Risk of Ischemic Stroke: a Meta-Analysis. 2007, Blood Coagulation & Fibrinolysis, 18 (5):497-504 (Impact Factor: 1.398, citations: 11)

97.   Marlien Pieters, Hester H. Vorster. Nutrition and hemostasis: A focus on urbanization in South Africa. Molecular Nutrition & Food Research. 2007

98.   Claes Ladenvall. GENETIC ASSOCIATION STUDIES IN STROKE. PhD Thesis, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at Göteborg University, Göteborg, Sweden

99.   Stanković S, Majkić-Singh N. Advances in the genetic basis of ischemic stroke. 2008; Journal of Medical Biochemistry 27 (2),123-134

100.                        Zorio, E., Gilabert-Estellés, J., España, F., Ramón, L.A., Cosín, R., Estellés, A. Fibrinolysis: The key to new pathogenic mechanisms. 2008; Current Medicinal Chemistry 15 (9), 923-929

101.                        Heil, J.W., Malinowski, L., Rinderknecht, A., Broderick, J.P., Franz, D. Use of intravenous tissue plasminogen activator in a 16-year-old patient with basilar occlusion. 2008, Journal of Child Neurology 23 (9), pp. 1049-1053

102.                        Asselbergs FW, Pattin K, Snieder H, Hillege HL, van Gilst WH, Moore JH. Genetic architecture of tissue-type plasminogen activator and plasminogen activator inhibitor-1. Semin Thromb Hemost. 2008;34(6):562-8.

103.                        Titlic M, Karaman K, Andelinovic S. Anterior ischemic optic neuropathy comorbid with Factor V Leiden and PAI-1 4G/5G mutation. Bratis Lek Listy, 2009, 110 (3): 192-194

104.                        Matarin M, Brown WM, Dena H, Britton A, De Vrieze FW, Brott TG, Brown RD Jr, Worrall BB, Case LD, Chanock SJ, Metter EJ, Ferruci L, Gamble D, Hardy JA, Rich SS, Singleton A, Meschia JF. Candidate gene polymorphisms for ischemic stroke. Stroke. 2009 Nov;40(11):3436-42.

105.                        Zateyshchikov DA, Brovkin AN, Chistiakov DA, Nosikov VV.. Advanced age, low left atrial appendage velocity, and Factor V promoter sequence variation as predictors of left atrial thrombosis in patients with nonvalvular atrial fibrillation. J Thromb Thrombolysis. 2010 Jan 16. [Epub ahead of print]

106.                        Bentley P, Peck G, Smeeth L, Whittaker J, Sharma P. Causal relationship of susceptibility genes to ischemic stroke: comparison to ischemic heart disease and biochemical determinants. PLoS One. 2010 Feb 9;5(2):e9136.

107.                        M.Yu. Gilyarov, E.B. Generozov, M.U. Magomadova, S.Yu. Moroshkina, T.V. Pogoda, P.A. Kostin, V.A. Sulimov, A.L. Syrkin HEREDITARY THROMBOPHILIAS AND THEIR INFLUENCE ON THE RISK OF STROKE IN PATIENTS WITH ATRIAL FIBRILLATION. J. Echocardiography (Russian) 2009, 56: 26-30

Tsantes AΕ, Nikolopoulos GΚ, Bagos PG, Rapti E, Mantzios G, Kapsimali V, Travlou A. Association between the Plasminogen Activator Inhibitor-1 4G/5G Polymorphism and  Venous Thrombosis: a Meta-Analysis. 2007, Thrombosis and Haemostasis, 97 (6): 907-13 (Impact Factor:  3.803, citations: 31)

108.                        HOU Xu-hui, DU Jian-shi, YIN Wei-tian. Transfect PAI siRNA into human aorta smooth muscle cells. Chinese Journal of Laboratory Diagnosis. 2007: 11(10)1993-1295

109.                        Schenk JF, Stephan B, Zewinger S, Speer T, Pindur G. Comparison of the plasminogen activator inhibitor-1 4G/5G gene polymorphism in females with venous thromboembolism during pregnancy or spontaneous abortion. Clin Hemorheol Microcirc. 2008; 39(1-4):329-32.

110.                        Picchi, A., Pasqualini, P., D'Aiello, I., Cortese, B., Micheli, A., Limbruno, U. Acute ST-elevation myocardial infarction in a 15-year-old boy with celiac disease and multifactorial thrombotic risk. 2008; Thrombosis and Haemostasis 99 (6), 1116-1118

111.                        Roux, A., Sanchez, O., Meyer, G. Which thrombophilia tests for patients suffering from venous thromboembolism disease? 2008; Reanimation 17 (4), 355-362

112.                        Sanna V, Zarrilli F, Nardiello P, D'Argenio V, Rocino A, Coppola A, Di Minno G, Castaldo G. Mutational spectrum of F8 gene and prothrombotic gene variants in haemophilia A patients from Southern Italy. Haemophilia. 2008

113.                        Seidel H. Significance of polymorphisms for arterial or venous thromboembolic risk. Predictive use of frequently determined polymorphisms GP Ia C807T, GP IIIa T1565C, PAI-1 675 4G/5G, and MTHFR C677T. MEDIZINISCHE GENETIK 20 (2): 223-229, 2008

114.                        Asselbergs, F.W., Pattin, K., Snieder, H., Hillege, H.L., Van Gilst, W.H., Moore, J.H. Genetic architecture of tissue-type plasminogen activator and plasminogen activator inhibitor-1 2008 Seminars in Thrombosis and Hemostasis 34 (6), pp. 562-568

115.                        Varga, E.A., Kerlin, B.A., Wurster, M.W. Social and ethical controversies in thrombophilia testing and update on genetic risk factors for venous thromboembolism               2008 Seminars in Thrombosis and Hemostasis 34 (6), pp. 549-561

116.                        Tsakiris, D.A., Tichelli, A. Thrombotic complications after haematopoietic stem cell transplantation: early and late effects, 2009, Best Practice and Research: Clinical Haematology 22 (1), pp. 137-145

117.                        Tukiainen E, Kylänpää ML, Repo H, Orpana A, Methuen T, Salaspuro M, Kemppainen E, Puolakkainen P. Hemostatic gene polymorphisms in severe acute pancreatitis. Pancreas. 2009 Mar;38(2):e43-6.

118.                        Mario D’Amico, Linda Pasta and Piero Sammarco. MTHFR C677TT, PAI1 4G-4G, V Leiden Q506, and prothrombin G20210A in hepatocellular carcinoma with and without portal vein thrombosis. Journal of Thrombosis and Thrombolysis 10.1007/s11239-008-0246-6

119.                        Titlic M, Karaman K, Andelinovic S. Anterior ischemic optic neuropathy comorbid with Factor V Leiden and PAI-1 4G/5G mutation. Bratis Lek Listy, 2009, 110 (3): 192-194

120.                        Bedencic M, Bozic M, Peternel P, Stegnar M. Major and Potential Prothrombotic Genotypes in Patients with Venous Thrombosis and in Healthy Subjects from Slovenia. Pathophysiol Haemos Thromb 2007/2008;36:58-63 (DOI: 10.1159/000173722)

121.                        Ringwald J, Berger A, Adler W, Kraus C, Pitto RP.   Genetic polymorphisms in venous thrombosis and pulmonary embolism after total hip arthroplasty: a pilot study. Clin Orthop Relat Res. 2009 ;467(6):1507-15.

122.                        Reverter, J.C., Tàssies, M.D. Genetic Aspects of the Antiphospholipid Syndrome: Association with Clinical Manifestations 2009 Handbook of Systemic Autoimmune Diseases 10, pp. 91-103

123.                        Zirlik, A., Ernst, S., Leugers, A., Willecke, F., Sobel, B.E., Bode, C., Nordt, T.K. Inhibition by fibrates of plasminogen activator inhibitor type-1 expression in human adipocytes and preadipocytes 2009 Thrombosis and Haemostasis 101 (6), pp. 1060-1069

124.                        Ma Z, Paek D, Oh CK. Plasminogen activator inhibitor-1 and asthma: role in the pathogenesis and molecular regulation CLINICAL AND EXPERIMENTAL ALLERGY 39 (8): 1136-1144 AUG 2009

125.                        Kanjaksha Ghosh, Shrimati Shettya and Sonal Voraa. Plasminogen activator inhibitor-1 4G/5G gene polymorphism in women with fetal loss. International Journal of Gynecology & Obstetrics, 2009

126.                        Dolors Tàssiesa, Merce Roqué, Joan Monteagudo, Teresa Martorell, Alessandro Sionis, Dabit Arzamendi, Magda Herasb and Joan-Carles Reverter. Thrombin-activatable fibrinolysis inhibitor genetic polymorphisms as markers of the type of acute coronary syndrome. Thrombosis Research Volume 124, Issue 5, November 2009, Pages 614-618

127.                        Li, Y., Bezemer, I.D., Rowland, C.M., Tong, C.H., Arellano, A.R., Catanese, J.J., Devlin, J.J., (...), Rosendaal, F.R. Genetic variants associated with deep vein thrombosis: The F11 locus  2009 Journal of Thrombosis and Haemostasis 7 (11), pp. 1802-1808

128.                        Castro-Marrero, J., Balada, E., Vilardell-Tarrés, M., Ordi-Ros, J. Genetic risk factors of thrombosis in the antiphospholipid syndrome 2009 British Journal of Haematology 147 (3), pp. 289-296

129.                        Krummenacher R, Lukas PS, Biasiutti FD, Begré S, Znoj H, Von Känel R. Independent association of sleep quality, fatigue, and vital exhaustion with platelet count in patients with a previous venous thromboembolic event. Platelets. 2009 Dec;20(8):566-74.

130.                        Hoekstra J, Guimarães AH, Leebeek FW, Darwish Murad S, Malfliet JJ, Plessier A, Hernandez-Guerra M, Langlet P, Elias E, Trebicka J, Primignani M, Garcia-Pagan JC, Valla DC, Rijken DC, Janssen HL; European Network for Vascular Disorders of the Liver (EN-Vie). Impaired fibrinolysis as a risk factor for Budd-Chiari syndrome. Blood. 2010 Jan 14;115(2):388-95. Epub 2009 Nov 18.

131.                        Morange, P.-E., Tregouet, D.-A Deciphering the molecular basis of venous thromboembolism: Where are we and where should we go?  2010  British Journal of Haematology 148 (4), pp. 495-506

132.                        Lee MH, Hammad SM, Semler AJ, Luttrell LM, Lopes-Virella MF, Klein RL. HDL3, but not HDL2, stimulates plasminogen activator inhibitor-1 release from adipocytes: the role of sphingosine-1-phosphate. J Lipid Res. 2010 Sep;51(9):2619-28. Epub 2010 Jun 3.

133.                        Lenicek Krleza J, Jakovljevic G, Bronic A, Coen Herak D, Bonevski A, Stepan-Giljevic J, Roic G. Contraception-related deep venous thrombosis and pulmonary embolism in a 17-Year-old girl heterozygous for factor V leiden, prothrombin G20210A mutation, MTHFR C677T and homozygous for PAI-1 mutation: report of a family with multiple genetic risk factors and review of the literature. Pathophysiol Haemost Thromb. 2010;37(1):24-9. Epub 2010 Jul 20.

134.                        Katrancioglu N, Manduz S, Ozen F, Yilmaz MB, Karahan O, Ozdemir O, Berkan O. Type I Plasminogen Activator Inhibitor 4G Allele Frequency is Associated with Chronic Venous Insufficiency. J Int Med Res. 2010 Jul-Aug;38(4):1513-8.

135.                        Zateyshchikov DA, Brovkin AN, Chistiakov DA, Nosikov VV. Advanced age, low left atrial appendage velocity, and Factor V promoter sequence variation as predictors of left atrial thrombosis in patients with nonvalvular atrial fibrillation. J Thromb Thrombolysis. 2010 Aug;30(2):192-9.

136.                        Bern, M.M., McCarthy, N.  Failure to lyse venous thrombi because of elevated plasminogen activator inhibitor 1 (PAI-1) and 4G polymorphism of its promotor genome (The PAI-1/4G syndrome) 2010, Clinical and Applied Thrombosis/Hemostasis 16 (5), pp. 574-578

137.                        Alfirevic, Z., Simundic, A.-M., Nikolac, N., Sobocan, N., Alfirevic, I., Stefanovic, M., Vucicevic, Z., Topic, E. Frequency of factor II G20210A, factor V Leiden, MTHFR C677T and PAI-15G/4G polymorphism in patients with venous thromboembolism: Croatian case-control study           2010 Biochemia Medica 20 (2), pp. 229-235

138.                        Manduz, S., Katrancioglu, N., Karahan, O., Ozdemir, O.             Association of the plasminogen activator inhibitor-1(PAI-1) gene 4G/5G promoter polymorphism in Buerger's disease (Tromboangiitis obliterans) 2010                 Health 2 (5), pp. 454-457

Bagos PG, Karnaouri AC, Nikolopoulos GK, Hamodrakas SJ.  No evidence for association of CTLA-4 gene polymorphisms with the risk of developing Multiple Sclerosis: a meta-analysis. 2007, Multiple Sclerosis, 13(2): 156-168 (Impact Factor: 3.312, citations: 11)

139.                        Stuart R, Lovett-Racke AE, Frohman EM, Hawker K, Racke MK.. Genetic analysis of the exon 1 position 49 CD152 dimorphism in multiple sclerosis. J Neuroimmunol. 2007; 191(1-2):45-50.

140.                        Luszczek W, Majorczyk E, Nockowski P, Pluciński P, Jasek M, Nowak I, Wiśniewski A, Kuśnierczyk P. Distribution of the CTLA-4 single nucleotide polymorphisms CT60G>A and +49A>G in psoriasis vulgaris patients and control individuals from a Polish Caucasian population. Int J Immunogenet. 2007

141.                        Svejgaard A. The immunogenetics of multiple sclerosis. Immunogenetics. 2008

142.                        Bye L, Modi N, Stanford MR, Kondeatis E, Vaughan R, Fortune F, Kanawati C, Ben-Chetrit E, Ghabra M, Murray PI, Wallace GR. CTLA-4 polymorphisms are not associated with ocular inflammatory disease. Tissue Antigens. 2008; 72(1):49-53.

143.                        Palacios R, Comas D, Elorza J, Villoslada P. Genomic regulation of CTLA4 and Multiple Sclerosis. J Neuroimmunol. 2008

144.                        Kleinschnitz C, Meuth SG, Wiendl PH. The trials and errors in MS therapy. Int MS J. 2008;15(3):79-90

145.                        M.R. Noori-Daloii, A. Heidari, M. Keramati-Pour, A.Rashidi-Nezhad, and A.A. Amirzargar. Lack of Association between Promoter Gene Polymorphism (-318 C/T) and Multiple Sclerosis in Iranian Population. Journal of Sciences (Islamic Republic of Iran) 19(1): 15-17 (2008)

146.                        Wang, J.-J., Jiang, L.-Q., He, B., Shi, K.-L., Li, J.-W., Zou, L.-P. The association of CTLA-4 and CD28 gene polymorphisms with idiopathic ischemic stroke in the paediatric population 2009 International Journal of Immunogenetics 36 (2), pp. 113-118

147.                        Holmoy T, Harbo H, Vartdal F, Spurkland A. Genetic and Molecular Approaches to the Immunopathogenesis of Multiple Sclerosis: An Update. CURRENT MOLECULAR MEDICINE 9 (5): 591-611 JUN 2009

148.                        Lidia  Karabon, Agata  Kosmaczewska, Malgorzata  Bilinska, Edyta  Pawlak, Lidia  Ciszak, Anna  Jedynak, Anna  Jonkisz, Leszek  Noga, Anna  Pokryszko-Dragan, Magdalena  Koszewicz and Irena  Frydecka. The CTLA-4 gene polymorphisms are associated with CTLA-4 protein expression levels in multiple sclerosis patients and with susceptibility to disease. Immunology.Volume 128 Issue 1pt2, Pages e787 - e796

149.                        Evsyukova, I., Somarelli, J.A., Gregory, S.G., Garcia-Blanco, M.A. Alternative splicing in multiple sclerosis and other autoimmune diseases 2010, RNA Biology 7 (4), pp. 462-473

Bagos PG, Nikolopoulos GK. A method for meta-analysis of case-control genetic association studies using logistic regression. 2007, Statistical Applications in Genetics and Molecular Biology, 6(1): Article 17 (Impact Factor: 1.773, citations: 13)

150.                        Curtin K, Wong J, Allen-Brady K, Camp NJ. PedGenie: meta genetic association testing in mixed family and case-control designs. BMC Bioinformatics. 2007;8:448.

151.                        Kauffman MA, Moron DG, Consalvo D, Bello R, Kochen S. Association study between interleukin 1 beta gene and epileptic disorders: a HuGe review and meta-analysis. Genet Med. 2008; 10(2):83-8.

152.                        Schunkert H, Götz A, Braund P, McGinnis R, Tregouet DA, Mangino M, Linsel-Nitschke P, Cambien F, Hengstenberg C, Stark K, Blankenberg S, Tiret L, Ducimetiere P, Keniry A, Ghori MJ, Schreiber S, El Mokhtari NE, Hall AS, Dixon RJ, Goodall AH, Liptau H, Pollard H, Schwarz DF, Hothorn LA, Wichmann HE, König IR, Fischer M, Meisinger C, Ouwehand W, Deloukas P, Thompson JR, Erdmann J, Ziegler A, Samani NJ; Cardiogenics Consortium. Repeated replication and a prospective meta-analysis of the association between chromosome 9p21.3 and coronary artery disease. Circulation. 2008; 117(13):1675-84

153.                        Linsel-Nitschke P, Götz A, Erdmann J, Braenne I, Braund P, Hengstenberg C, Stark K, Fischer M, Schreiber S, El Mokhtari NE, Schaefer A, Schrezenmeier J, Rubin D, Hinney A, Reinehr T, Roth C, Ortlepp J, Hanrath P, Hall AS, Mangino M, Lieb W, Lamina C, Heid IM, Doering A, Gieger C, Peters A, Meitinger T, Wichmann HE, König IR, Ziegler A, Kronenberg F, Samani NJ, Schunkert H; Wellcome Trust Case Control Consortium (WTCCC); Cardiogenics Consortium. Lifelong reduction of LDL-cholesterol related to a common variant in the LDL-receptor gene decreases the risk of coronary artery disease--a Mendelian Randomisation study. PLoS ONE. 2008; 3(8):e2986

154.                        Thum YM, Ahn S. Challenges of Meta-Analysis from the Standpoint of a Latent Variable Framework: A New Approach for Synthesizing the Results from Several Multiple Regressions. Technical Report. College of Education, Michigan State University, 2008

155.                        Ludwig A. Hothorn, Torsten Hothorn. Order-restricted Scores Test for the Evaluation of Population-based Case-control Studies when the Genetic Model is Unknown. Biometrical Journal, 2009, in press

156.                        Li H, Ha TC, Tai BC. XRCC1 gene polymorphisms and breast cancer risk in different populations: a meta-analysis. Breast. 2009; 18(3):183-91.

157.                        Bai J, Dai J, Yu H, Shen H, Chen F. Cigarette smoking, MDM2 SNP309, gene-environment interactions, and lung cancer risk: a meta-analysis. J Toxicol Environ Health A. 2009;72(11):677-82.

158.                        Andreas Ziegler, Inke R. König, Friedrich Pahlke. A Statistical Approach to Genetic Epidemiology: Concepts and Applications.Wiley-Blackwell, 2010

159.                         Alexis Elbaz, Owen A. Ross. John P.A. Ioannidis. Alexandra I Soto-Ortolaza, Frédéric Moisan, Jan Aasly, Grazia Annesi, Maria Bozi, Laura Brighina, Marie-Christine Chartier-Harlin, Alain Destée, Carlo Ferrarese, Alessandro Ferraris, J. Mark Gibson, Suzana Gispert, Georgios M. Hadjigeorgiou, Barbara Jasinska-Myga, Christine Klein, Rejko Krüger MD, Jean-Charles Lambert, Katja Lohmann, Simone van de Loo, Marie-Anne Loriot Pharm, Timothy Lynch, George D. Mellick, Eugénie Mutez, Christer Nilsson, Grzegorz Opala,. Andreas Puschmann, Aldo Quattrone, Manu Sharma, Peter A. Silburn, Leonidas Stefanis,. Ryan J. Uitti, Enza Maria Valente,. Carles Vilariño-Güell,. Karin Wirdefeldt,. Zbigniew K. Wszolek, Georgia Xiromerisiou, Demetrius M. Maraganore, Matthew J. Farrer. Independent and joint effects of the MAPT and SNCA genes in parkinson's disease. Annals of Neurology, 2010

160.                        Pereira TV, Patsopoulos NA, Pereira AC, Krieger JE. Strategies for genetic model specification in the screening of genome-wide meta-analysis signals for further replication. International Journal of Epidemiology, 2010

161.                        Tu Y, Cui G, Xu Y, Bao X, Wang X, Wang D: Genetic polymorphism of CYP11B2 gene and stroke in the Han Chinese population and a meta-analysis. Pharmacogenetics and Genomics 2011, 21:115-120.  

162.                         Baumgartner C, Osl M, Netzer M, Baumgartner D: Bioinformatic-driven search for metabolic biomarkers in disease. J Clin Bioinformatics 2011, 1:2.  

Nikolopoulos GΚ, Tsantes AΕ, Bagos PG, Travlou A, Vaiopoulos G. Integrin, alpha 2 gene C807T Polymorphism and Risk of Ischemic Stroke: a Meta-Analysis. 2007, Thrombosis Research; 119 (4): 501-510 (Impact Factor: 2.449, citations: 19)

163.                        van Rijn MJE, Dissecting the Genetics of Stroke, PhD Thesis, Erasmus Universiteit Rotterdam, 2007

164.                        Stanković S, Majkić-Singh N. Advances in the genetic basis of ischemic stroke. 2008; Journal of Medical Biochemistry 27 (2),123-134

165.                        Bersano A, Ballabio E, Bresolin N, Candelise L. Genetic polymorphisms for the study of multifactorial stroke. Hum Mutat. 2008;29(6):776-95

166.                        Vanessa Roldán, Francisco Marín, Rocío González-Conejero, Antonio García-Honrubia, Silvia Martí, Aranzazu Alfaro, Mariano Valdés, Javier Corral, Gregory Y. H. Lip, Vicente Vicente. Factor VII -323 decanucleotide D/I polymorphism in atrial fibrillation: Implications for the prothrombotic state and stroke risk. Annals of Medicine, 2008

167.                        Seidel H. Significance of polymorphisms for arterial or venous thromboembolic risk. Predictive use of frequently determined polymorphisms GP Ia C807T, GP IIIa T1565C, PAI-1 675 4G/5G, and MTHFR C677T. MEDIZINISCHE GENETIK 20 (2): 223-229, 2008

168.                        Feher, G., Feher, A., Pusch, G., Lupkovics, G., Szapary, L., Papp, E. The genetics of antiplatelet drug resistance 2009 Clinical Genetics 75 (1), pp. 1-18

169.                        Kvasnička, J., Hájková, J., Bobčíková, P., Dušková, D., Poletínová, Š., Kieferová, V., Zenáhlíková, Z., Pecen, L. Platelet gene polymorphisms related to atherothrombogenesis and their frequencies in the healthy middle-aged Czech population 2009 Cor et Vasa 51 (3), pp. 187-193

170.                        Yumiko Matsubara, Mitsuru Murata and Yasuo Ikeda. Polymorphisms of Platelet Membrane Glycoproteins. In: Recent Advances in Thrombosis and Hemostasis 2008

171.                        Alberts MJ. Stroke genomics. In Cardiovascular Genetics and Genomics, (Ed) Dan M. Roden. 2009

172.                        Khan Y, Faraday N, Herzog W, Shuldiner AR. Genetic determinants of arterial thrombosis. In Cardiovascular Genetics and Genomics, (Ed) Dan M. Roden. 2009

173.                        Gerald  Bertrand, Vincent  Jallu, Dominique  Saillant, Dominique  Kervran, Corinne  Martageix, and Cecile  Kaplan. The new platelet alloantigen Caba: a single point mutation Gln716His on the α2 integrin. Transfusion, 2009, Volume 49 Issue 10, Pages 2076 – 2083

174.                        Matarin M, Brown WM, Dena H, Britton A, De Vrieze FW, Brott TG, Brown RD Jr, Worrall BB, Case LD, Chanock SJ, Metter EJ, Ferruci L, Gamble D, Hardy JA, Rich SS, Singleton A, Meschia JF. Candidate gene polymorphisms for ischemic stroke. Stroke. 2009 Nov;40(11):3436-42.

175.                        R Coppo, J Feehally Is progression of IgA nephropathy conditioned by genes regulating atherosclerotic damage? Nephrology Dialysis Transplantation, 2009.

176.                        Matarin, M., Singleton, A., Hardy, J., Meschia, J. The genetics of ischaemic stroke.2010, Journal of Internal Medicine 267 (2), pp. 139-155

177.                        Nissinen, L., Pentikäinen, O.T., Jouppila, A., Käpylä, J., Ojala, M., Nieminen, J., Lipsanen, A., (...), Heino, J. A small-molecule inhibitor of integrin α2β1 introduces a new strategy for antithrombotic therapy. 2010, Thrombosis and Haemostasis 103 (2), pp. 387-397

178.                        Fan Az, Fang Y, Yesupriva A, Chang MH, Kilmer G, House M, Hayes D, Ned RM, Dowling NF, Mokdad AH. Gene polymorphisms in association with self-reported stroke in US adults. The Application of Clinical Genetics. 2010:3 23–28

179.                        Stankovic S, Majkic-Singh N. Genetic aspects of ischemic stroke: coagulation, homocysteine, and lipoprotein metabolism as potential risk factors. Crit Rev Clin Lab Sci. 2010;47(2):72-123. Review.

180.                        Pavkovic, M., Petlichkovski, A., Stojanovic, A., Trajkov, D., Spiroski, M. BGL II polymorhism of the α2β1 integrin gene in Macedonian population 2010 Macedonian Journal of Medical Sciences 3 (2), pp. 119-122

181.                        Novel Insights into Genetics of Arterial Thrombosis

182.                        Joke Konings, José W. P. Govers-Riemslag and Hugo ten Cate. Novel Insights into Genetics of Arterial Thrombosis CLINICAL CARDIOGENETICS 2011, Part 5, 331-351, DOI: 10.1007/978-1-84996-471-5_21

Tsantes AΕ, Nikolopoulos GΚ, Bagos PG, Vaiopoulos G, Travlou A. Lack of association between the platelet glycoprotein Ia C807T gene polymorphism and coronary artery disease: a meta-analysis. 2007, International Journal of Cardiology, 118 (2):189-196 (Impact Factor: 2.878, citations: 5)

183.                        Surin WR, Barthwal MK, Dikshit M. Platelet collagen receptors, signaling and antagonism: Emerging approaches for the prevention of intravascular thrombosis., Thromb Res. 2007, in press

184.                        Gršković, B., Pašalić, D., Ferenčak, G., Stavljenić-Rukavina, A. Influence of gene polymorphisms in adhesion molecules and inflammation mediators as risk factors for coronary heart disease and myocardial infarction - An overview. 2008, Acta Medica Croatica 62 (1), pp. 41-52

185.                        Yumiko Matsubara, Mitsuru Murata and Yasuo Ikeda. Polymorphisms of Platelet Membrane Glycoproteins. In: Recent Advances in Thrombosis and Hemostasis 2008

186.                        Kvasnička, J., Hájková, J., Bobčíková, P., Dušková, D., Poletínová, Š., Kieferová, V., Zenáhlíková, Z., Pecen, L. Platelet gene polymorphisms related to atherothrombogenesis and their frequencies in the healthy middle-aged Czech population Cor et Vasa 51 (3), pp. 187-193   2009

187.                        Gerald  Bertrand, Vincent  Jallu, Dominique  Saillant, Dominique  Kervran, Corinne  Martageix, and Cecile  Kaplan. The new platelet alloantigen Caba: a single point mutation Gln716His on the α2 integrin. Transfusion, 2009, Volume 49 Issue 10, Pages 2076 - 2083       

Valavanis IK, Bagos PG, Emiris IZ. β-barrel Transmembrane Proteins: Geometric Modelling, Detection of Transmembrane Region, and Structural Properties. Computational Biology and Chemistry, 2006, 30(6):416-24 (Impact Factor: 1.837, citations: 5)

188.                        M.S. Gelfand, D. Rodionov, Comparative genomics and functional annotation of bacterial transporters, Physics of Life Reviews (2008), 5(1), pp. 22-49

189.                        Scott KA, Bond PJ, Ivetac A, Chetwynd AP, Khalid S, Sansom MS. Coarse-Grained MD Simulations of Membrane Protein-Bilayer Self-Assembly. Structure. 2008;16(4):621-630.

190.                        Jing Hu. Prediction of Protein Function and Functional Sites from Protein Sequences. PhD Thesis. Utah State University. 2009

191.                        Benedito VA, Li H, Dai X, Wandrey M, He J, Kaundal R, Torres-Jerez I, Gomez SK, Harrison MJ, Tang Y, Zhao PX, Udvardi MK. Genomic inventory and transcriptional analysis of Medicago truncatula transporters Plant Physiol. 2010;152(3):1716-30.

192.                        Kik, R.A., Leermakers, F.A.M., Kleijn, J.M. Molecular modeling of proteinlike inclusions in lipid bilayers: Lipid-mediated interactions 2010 Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 81 (2), art. no. 021915

Petsalaki ΕΙ, Bagos PG, Litou ΖΙ, Hamodrakas SJ.  PredSL: A tool for the N-terminal sequence-based prediction of subcellular location. 2006, Genomics Proteomics and Bioinformatics, 4(1); 48-55 (Impact Factor: -, citations: 18)

193.                        Schwacke R. Fischer K, Ketelsen B, Krupinska K, Krause K. Comparative survey of plastid and mitochondrial targeting properties of transcription factors in Arabidopsis and rice. Molecular Genetics and Genomics. 277 (6): 631-646

194.                        Klee EW, Sosa CP. Computational classification of classically secreted proteins. 2007, Drug Discovery Today 12 (5-6): 234-240

195.                        Kirchberger S, Leroch M, Huynen MA, Wahl M, Neuhaus HE, Tjaden J. Molecular and biochemical analysis of the plastidic ADP-glucose transporter (ZmBT1) from Zea mays. J Biol Chem. 2007;282(31):22481-91

196.                        Zhao X, de Palma J, Oane R, Gamuyao R, Luo M, Chaudhury A, Hervé P, Xue Q, Bennett J. OsTDL1A binds to the LRR domain of rice receptor kinase MSP1, and is required to limit sporocyte numbers. Plant J. 2008;54(3):375-87

197.                        Aarti Garg and Gajendra P. S. Raghava. A machine learning based method for the prediction of secretory proteins using amino acid composition, their order and similarity-search. In Silico Biology 8, 0012 (2008)

198.                        Rokov-Plavec J, Dulic M, Duchêne AM, Weygand-Durasevic I. Dual targeting of organellar seryl-tRNA synthetase to maize mitochondria and chloroplasts. Plant Cell Rep. 2008;27(7):1157-68

199.                        Schliebner, I.; Pribil, M.; Zuhlke, J.; Dietzmann, A.; Leister, D. A Survey of Chloroplast Protein Kinases and Phosphatases in Arabidopsis thaliana. Current Genomics, 9(3), 2008;184-190(7)

200.                        Alves, Rui; Vilaprinyo, Ester; Sorribas, Albert.  Integrating Bioinformatics and Computational Biology: Perspectives and Possibilities for In Silico Network Reconstruction in Molecular Systems Biology. Current Bioinformatics, 3(2), 2008; 98-129(32)

201.                        Yu QB, Li G, Wang G, Sun JC, Wang PC, Wang C, Mi HL, Ma WM, Cui J, Cui YL, Chong K, Li YX, Li YH, Zhao Z, Shi TL, Yang ZN. Construction of a chloroplast protein interaction network and functional mining of photosynthetic proteins in Arabidopsis thaliana. Cell Res. 2008; 18(10):1007-19.

202.                        Gschloessl B, Guermeur Y, Cock JM. HECTAR: a method to predict subcellular targeting in heterokonts. BMC Bioinformatics. 2008; 9(1):393.

203.                        Zhang, S.-B., Lai, J.-H., He, J.-G. A novel approach for prediction of protein subcellular localization using optimal local information 2008 Zhongshan Daxue Xuebao/Acta Scientiarum Natralium Universitatis Sunyatseni 47 (6), pp. 16-21

204.                        Yoshie S. Momonoki, Kosuke Yamamoto and Suguru Oguri. Molecular Cloning of Oxygen-Evolving Enhancer Genes Induced by Salt Treatment in a Halophyte, Salicornia europaea L. Plant Production Science. 12 (2009) , No. 2 193-198

205.                        Blum T, Briesemeister S, Kohlbacher O. MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction BMC Bioinformatics. 2009;10:274.

206.                        Briesemeister S, Rahnenführer J, Kohlbacher O. Going from where to why--interpretable prediction of protein subcellular localization. Bioinformatics.  2010;26(9):1232-8.

207.                        Briesemeister S, Rahnenführer J, Kohlbacher O. YLoc--an interpretable web server for predicting subcellular localization. Nucleic Acids Res. 2010. [Epub ahead of print]

208.                        Zhang X, Cui J, Nilsson D, Gunasekera K, Chanfon A, Song X, Wang H, Xu Y, Ochsenreiter T. The Trypanosoma brucei MitoCarta and its regulation and splicing pattern during development. Nucleic Acids Res. 2010 Jul 26. [Epub ahead of print]

209.                        Lee YH, Tan AT, Chung MC. Subcellular fractionation methods and strategies for proteomics. Proteomics, 2010

210.                        Gabilly ST, Dreyfuss BW, Karamoko M, Corvest V, Kropat J, Page MD, Merchant SS, Hamel PP. CCS5, a thioredoxin-like protein involved in the assembly of plastid c-type cytochromes. J Biol Chem. 2010 Sep 24;285(39):29738-49. Epub 2010 Jul 13.

Liappas I, Chatzipanagiotou S, Nicolaou C, Tzavellas E, Bagos P, Soldatos CR. Interrelation of Hepatic Function, Thyroid Activity and Mood Status of Alcohol-dependent Individuals. In Vivo. 2006; 20(2): 293-300. (Impact Factor: 0.99, citations: 2)

211.                        Bitri L, Dhaouadi N, Ouertani L, Maurel D, Ben Saad M. Toxicity of hexachlorobenzene in Meriones unguiculatus: effects on thyroid and liver. Comptes Rendus – Biologies, 330 (5), 2007: 410-418

212.                        G. A. Barclay, J. Barbour, S. Stewart, C. P. Day and E. Gilvarry Adverse physical effects of alcohol misuse Advances in Psychiatric Treatment (2008) 14: 139-151

Bagos PG, Liakopoulos TD, Hamodrakas SJ. Algorithms for incorporating prior topological information in HMMs: Application to transmembrane proteins.  2006, BMC Bioinformatics; 7:189 (Impact Factor: 3.49, citations: 18)

213.                        Madhavi K. Ganapathiraju. Application of Language Technologies in Biology: Feature Extraction and Modeling for Transmembrane Helix Prediction. PhD Thesis, Carnegie Mellon University, 2007

214.                        Planchon S, Chambon C, Desvaux M, Chafsey I, Leroy S, Talon R, Hébraud M. Proteomic analysis of cell envelope from Staphylococcus xylosus C2a, a coagulase-negative staphylococcus. J Proteome Res. 2007;6(9):3566-80

215.                        Jing Hu and Changhui Yan. HMM_RA: An Improved Method for Alpha-Helical Transmembrane Protein Topology Prediction. Bioinformatics and Biology Insights 2008:2, 67-74

216.                        Merlino A, Varriale S, Coscia MR, Mazzarella L, Oreste U. Structure and dimerization of the teleost transmembrane immunoglobulin region. J Mol Graph Model. 2008 Jul 22

217.                        Vasilakos AV, Spyrou G Computational Intelligence in Medicine and Biology: A Survey  JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE 5 (12): 2365-2376 2008

218.                        Lin F, Wang RX Molecular modeling of the three-dimensional structure of GLP-1R and its interactions with several agonists  JOURNAL OF MOLECULAR MODELING 15 (1): 53-65 2009

219.                        Nugent, T., Jones, D.T. Transmembrane protein topology prediction using support vector machines 2009 BMC Bioinformatics 10, art. no. 159

220.                        De Grassi A, Ciccarelli FD. Tandem repeats modify the structure of human genes hosted in segmental duplications. Genome Biol. 2009;10(12):R137

221.                        Sami Laroum Dominique Tessier, B´eatrice Duval, and Jin-Kao Hao. A Local Search Appproach for Transmembrane Segment and Signal Peptide Discrimination. In C. Pizzuti, M.D. Ritchie, and M. Giacobini (Eds.): EvoBIO 2010, LNCS 6023, pp. 134–145, 2010., Springer-Verlag Berlin Heidelberg 2010

222.                        Choudry AR, Novic M. Data-driven model for the prediction of protein transmembrane regions. SAR and QSAR in Environmental Research, Volume 20, Issue 7 & 8 October 2009 , pages 741 – 754

223.                        Goudenège, D., Avner, S., Lucchetti-Miganeh, C., Barloy-Hubler, F. CoBaltDB: Complete bacterial and archaeal orfeomes subcellular localization database and associated resources. 2010 BMC Microbiology 10, art. no. 88

224.                        Pylouster J, Bornot A, Etchebest C, de Brevern AG. Influence of assignment on the prediction of transmembrane helices in protein structures. Amino Acids. 2010 Mar 28. [Epub ahead of print]

225.                        Desvaux M, Hebraud M. Analysis of Cell Envelope proteins. In Handbook of Listeria monomytogenes. Liu D (Ed). pp. 359-384

226.                        Tusnady GE, Simon I. Shedding light on transmembrane topology. In: Introduction to Protein Structure prediction, Huzefa Rangwala, George Karypis (Eds). 2010

227.                        Daniel E. Westholm, Jacob D. Marold, Kevin J. Viken, Alicia H. Duerst, Grant W. Anderson, and Jon N. Rumbley Evidence of Evolutionary Conservation of Function between the Thyroxine Transporter Oatp1c1 and Major Facilitator Superfamily Members. Endocrinology, 2010

228.                        Tusnady GE, Simon I. Topology Prediction of Helical Transmembrane Proteins: How Far Have We Reached? Current Protein and Peptide Science, Volume 11, Number 7, November 2010 , pp. 550-561(12)

229.                        Tusnady GE, Simon I Resource for structure related information on transmembrane proteins.  In Structural Bioinformatics of Membrane Proteins (Ed. Dmitrij Frishman) 2010

230.                        Janusz M. Bujnicki. First Steps of Protein Structure Prediction. In Karolina Majorek, Łukasz Kozłowski, Marcin Jąkalski2 Janusz M. Bujnicki (Eds) Prediction of Protein Structures, Functions, and Interactions © 2009 John Wiley & Sons, Ltd

Bagos PG, Nikolopoulos G, Ioannidis A. Chlamydia pneumoniae infection and the risk of multiple sclerosis: a meta-analysis. Multiple Sclerosis 2006, 12(4), 397-411 (Impact Factor: 3.312, citations: 21)

231.                        Stratton CW, Wheldon DB. Multiple sclerosis: an infectious syndrome involving Chlamydophila pneumoniae. Trends Microbiol. 2006; 14(11): 474-9

232.                        [Editorial-Research Highlights]. An association between Chlamydia pneumoniae and multiple sclerosis. Nature Clinical Practice Neurology (2006) 2, 467-468

233.                        Ascherio A, Munger KL. Environmental risk factors for multiple sclerosis. Part I: The role of infection. 2007; Annals of Neurology 61 (4): 288-299

234.                        Krone B, Pohl D, Rostasy K, Kahler E, Brunner E, Oeffner F, Grange JM, Gartner J, Hanefeld F. Common infectious agents in multiple sclerosis: a case control study in children. Mult Scler. 2008;14(1):136-9

235.                        Fainardi, Enrico; Castellazzi, Massimiliano; Seraceni, Silva; Granieri, Enrico; Contini, Carlo. Under the Microscope: Focus on Chlamydia pneumoniae Infection and Multiple Sclerosis. Current Neurovascular Research, Volume 5, Number 1, February 2008 , pp. 60-70(11)

236.                        Pordeus V, Szyper-Kravitz M, Levy RA, Vaz NM, Shoenfeld Y. Infections and Autoimmunity: A Panorama. Clin Rev Allergy Immunol. 2008

237.                        Contini C, Seraceni S, Cultrera R, Castellazzi M, Granieri E, and E Fainardi. Molecular detection of Parachlamydia-like organisms in cerebrospinal fluid of patients with multiple sclerosis. Multiple Sclerosis, 2008; 14(4): 564 – 566

238.                        Rýzlová, M., Gregor, P. Acute pericarditis as an organic manifestation of the acute infection Chlamydia pneumoniae. 2008; Vnitrni Lekarstvi 54 (9), pp. 866-870

239.                        Sessa, R., Cipriani, P., di Pietro, M., Schiavoni, G., Santino, I., del Piano, M. Chlamydia pneumoniae and chronic diseases with a great impact on public health, 2008, International Journal of Immunopathology and Pharmacology 21 (4), pp. 1041-1043

240.                        Thornton AE, DeFreitas VG. The Neuropsychology of Multiple Sclerosis. In “Neuropsychological Assessment of Neuropsychiatric and Neuromedical Disorders” Igor Grant, Kenneth M. Adams, Kenneth Adams (Eds) Edition: 3, Published by Oxford University Press US, 2009

241.                        Giuseppe Giocoli, Cornelis J. Biesheuvel, Heather F. Gidding and David Andresen. Advances in diagnostics for microbial agents: can clinical validation keep pace with the technical promises? Ann Ist Super Sanità 2009 | Vol. 45, No. 2: 168-172

242.                        Krone, B., Oeffner, F., Grange, J.M Is the risk of multiple sclerosis related to the 'biography' of the immune system? 2009 Journal of Neurology 256 (7), pp. 1052-1060

243.                        Beagley, K., Huston, W.M., Hansbro, P.M., Timms, P. Chlamydial infection of immune cells: Altered function and implications for disease 2009 Critical Reviews in Immunology 29 (4), pp. 275-305

244.                        Bekir Kocazeybek, Belma Karatoka, Ayse Altıntas, Mustafa Aslan, Suat Saribas, Jale Agaoglu, Sevgi Ergin, Vedat Koksal, Ahmet Dirican and Sabahattin Saib. Infection and genotype relationship in multiple sclerosis: Do Chlamydophila pneumoniae and human herpes virus-6 infections together with APO E alleles have a role in the etiopathogenesis of multiple sclerosis? African Journal of Microbiology Research Vol. 3(9) pp. 565-571 , September, 2009

245.                        Fainardi E, Castellazzi M, Tamborino C, Seraceni S, Tola MR, Granieri E, Contini C. Chlamydia pneumoniae-specific intrathecal oligoclonal antibody response is predominantly detected in a subset of multiple sclerosis patients with progressive forms. J Neurovirol. 2010 Jan 6. [Epub ahead of print]

246.                        Carlo Contini., Silva Seraceni., Rosario Cultrera., Massimiliano  Castellazzi., Enrico Granieri., Enrico Fainardi. Chlamydophila pneumoniae infection and its role in neurological disorders. Interdisciplnary Perspectives on Infectious Diseases. 2009

247.                        Sunita Venkateswaran, Brenda Banwell Pediatric multiple sclerosis. Neurologist. 2010 (2):92-105

248.                        Klaus Lauer; Environmental risk factors in multiple sclerosis Expert Rev Neurother. 2010 Mar ;10 (3):421-40

249.                        Strobl, Dominika (2010) Stillen und jahreszeitenabhängige Geburtenrate bei Patienten mit Multipler Sklerose. PhD Thesis, Universität Regensburg

250.                        Siddharama Pawate and Subramaniam Sriram The role of infections in the pathogenesis and course of multiple sclerosis. Ann Indian Acad Neurol. 2010 Apr–Jun; 13(2): 80–86.

251.                        Griffith, Joanna Elizabeth. Studies into the diagnosis, treatment and management of chlamydiosis in koalas. University of Sydney. Faculty of Veterinary Science. PhD Thesis, 2010

Sgourakis NG, Bagos PG, Hamodrakas SJ. Prediction of the coupling specificity of GPCRs to four families of G-proteins using Hidden Markov Models and Artificial Neural Networks. Bioinformatics, 2005, 21(22): 4101-6. (Impact Factor: 4.328, citations: 22)

252.                        Ono T, Hishigaki H. Prediction of GPCR-G Protein Coupling Specificity Using Features of Sequences and Biological Functions. Genomics, Proteomics and Bioinformatics. 2006. 4 (4), 238-244

253.                        Jiang Z, Guan C, Zhou Y. Computational prediction of the coupling specificity of g protein-coupled receptors. Appl Biochem Biotechnol. 2007;141 (1):109-18.

254.                        Ganga D. Ghimire, Kenichiro Imai, Fumitsugu Akazawa, Toshiyuki Tsuji, Masashi Sonoyama and Shigeki Mitaku. Physicochemical properties of amino acid sequences of G-proteins for understanding GPCR-G-protein coupling. 2006; Chem-Bio Informatics Journal: 6(1) 1-16

255.                        Mann S, Li J, Chen YP. A pHMM-ANN based discriminative approach to promoter identification in prokaryote genomic contexts. Nucleic Acids Res. 2006

256.                        Christopher H. Bryant, Daniel C. Fredouille, Alex Wilson, Channa K. Jayawickreme, Steven Jupe and Simon Topp. Pertinent Background Knowledge for Learning Protein Grammars. Lecture Notes in Computer Science, 4212 LNAI, 54-65

257.                        Jiang ZR, Zhou YH. Using silico methods predicting ligands for orphan GPCRs. Curr Protein Pept Sc, 2006; 7(5): 459-464

258.                        Peirson S, Foster RG. Melanopsin: another way of signaling light. Neuron. 2006; 49(3):331-9

259.                        Jacques Haiech, Jean-Luc Galzi, Marie-Claude Kilhoffer, Marcel Hibert, Didier Rognan. Why G Protein-coupled Receptors Databases are Needed. In Raimund Mannhold, Hugo Kubinyi, Gerd Folkers (Eds).  Ligand Design for G Protein-coupled Receptors. 2006 Wiley, 2; 27-38

260.                        Promponas VJ. Genomes, Genes, Proteins and Computers. Computational Molecular Biology and Bioinformatics. UPGRADE Vol. VII, No. 1, 2006 47-52

261.                        Lu F, Li J, Jiang Z. Computational identification and analysis of G protein-coupled receptor targets. Drug Development Research. 67(10): 771 – 780

262.                        Quaynor S, Hu L, Leung PK, Feng H, Mores N, Krsmanovic LZ, Catt KJ. Expression of a Functional GPR54-Kisspeptin Autoregulatory System in Hypothalamic GnRH Neurons. Mol Endocrinol. 2007

263.                        Muramatsu T. Studies on the prediction of membrane protein function from protein sequence. 2006, PhD Thesis, Nara Institute of Science and Technology.

264.                        Quaynor S, Hu L, Leung PK, Feng H, Mores N, Krsmanovic LZ, Catt KJ. Expression of a functional g protein-coupled receptor 54-kisspeptin autoregulatory system in hypothalamic gonadotropin-releasing hormone neurons. Mol Endocrinol. 2007;21(12):3062-70

265.                        Sandra Siehler, G12/13-dependent signaling of G-protein-coupled receptors: disease context and impact on drug discovery. Expert Opinion on Drug Discovery 2007, Vol. 2, No. 12, Pages 1591-1604

266.                        Shimamura T, Hiraki K, Takahashi N, Hori T, Ago H, Masuda K, Takio K, Ishiguro M, Miyano M. Crystal structure of squid rhodopsin with intracellularly extended cytoplasmic region.  JOURNAL OF BIOLOGICAL CHEMISTRY 283 (26): 17753-17756 JUN 27 2008

267.                        Gu, Q., Ding, Y.-S., Zhang, T.-L. Prediction of G-protein-coupled receptor classes with pseudo amino acid composition.2nd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2008, art. no. 4535095, pp. 876-879

268.                        Gookin TE, Kim J, Assmann SM. Whole proteome identification of plant candidate G-protein coupled receptors in Arabidopsis, rice, and poplar: computational prediction and in-vivo protein coupling. Genome Biol. 2008;9(7):R120

269.                        Leung T, Humbert JE, Stauffer AM, Giger KE, Chen H, Tsai HJ, Wang C, Mirshahi T, Robishaw JD. The orphan G protein-coupled receptor 161 is required for left-right patterning Dev Biol. 2008;323(1):31-40.

270.                        Park, H.-C., Eo, H.-S., Kim, W. A computational approach for the classification of protein tyrosine kinases 2009 Molecules and Cells 28 (3), pp. 195-200

271.                        Krsmanovic, L.Z., Hu, L., Leung, P.-K., Feng, H., Catt, K.J. The hypothalamic GnRH pulse generator: multiple regulatory mechanisms 2009 Trends in Endocrinology and Metabolism 20 (8), pp. 402-408

272.                        Siehler, S. Regulation of RhoGEF proteins by G12/13-coupled receptors 2009 British Journal of Pharmacology 158 (1), pp. 41-49

273.                        Gu, Q., Ding, Y. Binary particle swarm optimization based prediction of G-protein-coupled receptor families with feature selection 2009 World Summit on Genetic and Evolutionary Computation, 2009 GEC Summit - Proceedings of the 1st ACM/SIGEVO Summit on Genetic and Evolutionary Computation, GEC'09, pp. 171-176

Sgourakis NG, Bagos PG, Papasaikas PK, Hamodrakas SJ. Prediction of GPCRs coupling specificity to G-proteins using refined profile hidden Markov models.  BMC Bioinformatics, 2005, 6:104. (Impact Factor: 3.781, citations: 24)

274.                        Guan CP, Jiang ZR, Zhou YH. Predicting the coupling specificity of GPCRs to G-proteins by support vector machines. Genomics Proteomics Bioinformatics. 2005; 3(4): 247-51

275.                        Guo Y, Li M, Lu M, Wen Z, Huang Z. Predicting G-protein coupled receptors-G-protein coupling specificity based on autocross-covariance transform. Proteins. 2006; 65(1): 55-60.

276.                        Ono T, Hishigaki H. Prediction of GPCR-G Protein Coupling Specificity Using Features of Sequences and Biological Functions. Genomics, Proteomics and Bioinformatics. 2006. 4 (4), 238-244

277.                        Jiang Z, Guan C, Zhou Y. Computational prediction of the coupling specificity of G protein-coupled receptors. Appl Biochem Biotechnol. 2007;141 (1):109-18.

278.                        Peirson S, Foster RG. Melanopsin: another way of signaling light. Neuron. 2006; 49(3):331-9

279.                        Wicher D, Agricola HJ, Sohler S, Gundel M, Heinemann SH, Wollweber L, Stengl M, Derst C. Differential receptor activation by cockroach adipokinetic hormones produces differential effects on ion currents, neuronal activity, and locomotion. J Neurophysiol. 2006; 95(4): 2314-25

280.                        Muramatsu T, Suwa M. Statistical analysis and prediction of functional residues effective for GPCR-G-protein coupling selectivity. Protein Engineering, Design and Selection. 2006; 19: 277-283.

281.                        Jacques Haiech, Jean-Luc Galzi, Marie-Claude Kilhoffer, Marcel Hibert, Didier Rognan. Why G Protein-coupled Receptors Databases are Needed. In Raimund Mannhold, Hugo Kubinyi, Gerd Folkers (Eds).  Ligand Design for G Protein-coupled Receptors. 2006 Wiley, 2; 27-38

282.                        Suga H, Haga T. Ligand screening system using fusion proteins of G protein-coupled receptors with G protein α subunits. Neurochemistry International 2007, 51 (2-4 SPEC. ISS.): 140-164

283.                        Muramatsu T. Studies on the prediction of membrane protein function from protein sequence. 2006, PhD Thesis, Nara Institute of Science and Technology.

284.                        Davies MN, Gloriam DE, Secker A, Freitas AA, Mendao M, Timmis J, Flower DR. Proteomic applications of automated GPCR classification. Proteomics. 2007;7(16):2800-14.

285.                        B.M. Groenendijk. Uncovering the Classification Characteristics of Olfactory G Protein-Coupled Receptors. MSc Thesis, 2007. University of Leiden, The Netherlands

286.                        Kuo-Li Chiang. Human LTR classification and prediction using Profile Hidden Markov Models. MSc Thesis, 2007, Department of Computer Science and Information Engineering National Central University, Taiwan

287.                        Miller GK, Fridell SL. A Forgotten Discrete Distribution? Reviving the Negative Hypergeometric Model. The American Statistician, Volume 61, Number 4, November 2007 , pp. 347-350(4)

288.                        Wicher D, Derst C, Gautier H, Lapied B, Heinemann SH, Agricola HJ. The satiety signaling neuropeptide perisulfakinin inhibits the activity of central neurons promoting general activity Frontiers in Cellular Neuroscience,  2008; in press

289.                        Jens Lättig. Investigations of Interactions of G Protein-Coupled Receptors with Their Ligands and G Proteins. PhD Thesis, 2008, Fachbereich Biologie, Chemie, Pharmazie, Freie Universität Berlin

290.                        Juan Carlos Mobarec‌, Marta Filizola. Advances in the development and application of computational methodologies for structural modeling of G-protein-coupled receptors. Expert Opinion on Drug Discovery 2008, 3(3): 343-355

291.                        Tagore S, Gomase VS, De RK. Pathway Modeling: New face of Graphical Probabilistic Analysis. J. Proteomics Bioinformatics Volume 1(5): 281-286(2008) – 281

292.                        Gu, Q., Ding, Y.-S., Zhang, T.-L. Prediction of G-protein-coupled receptor classes with pseudo amino acid composition.2nd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2008, art. no. 4535095, pp. 876-879

293.                        Ghimire, G.D., Tanizawa, H., Sonoyama, M., Mitaku, S. Physicochemical properties of GPCR amino acid sequences for understanding GPCR-G-protein coupling, 2008, Chem-Bio Informatics Journal 8 (2), pp. 49-57

294.                        Matthew N Davies, Andrew Secker, Mark Halling-Brown, David S Moss, Alex A Freitas, Jon Timmis, Edward Clark and Darren R Flower. GPCRTree: online hierarchical classification of GPCR function. BMC Research Notes 2008, 1:67

295.                        Park, H.-C., Eo, H.-S., Kim, W. A computational approach for the classification of protein tyrosine kinases 2009 Molecules and Cells 28 (3), pp. 195-200

296.                        Van Horn WD, Beel AJ, Kang C, Sanders CR. The impact of window functions on NMR-based paramagnetic relaxation enhancement measurements in membrane proteins. Biochim Biophys Acta. 2010 Feb;1798(2):140-9. Epub 2009 Sep 12.

297.                        Gu Q, Ding YS, Zhang TL. Prediction of G-protein-coupled receptor classes in low homology using Chou's pseudo amino acid composition with approximate entropy and hydrophobicity patterns. Protein Pept Lett. 2010 May;17(5):559-67.

Bagos PG, Liakopoulos TD, Hamodrakas SJ. Evaluation of methods for predicting the topology of ß-barrel outer membrane proteins and a consensus prediction method. BMC Bioinformatics, 2005, 6:7. (Impact Factor: 3.781, citations: 42)

298.                        Gromiha MM, Ahmad S. Suwa M. TMBETA-NET: discrimination and prediction of membrane spanning ß-strands in outer membrane proteins. Nucleic Acids Research 2005 33(Web Server issue):W164-W167

299.                        Forrest LR, Tang CL, Honig B. On the accuracy of homology modeling and sequence alignment methods applied to membrane proteins. Biophys J. 2006 91(2):508-17.

300.                        Pajon R, Yero D, Lage A, Llanes A, Borroto CJ. Computational identification of beta-barrel outer-membrane proteins in Mycobacterium tuberculosis predicted proteomes as putative vaccine candidates. Tuberculosis 86 (3-4): 290-302; 2006

301.                        Martin J., de Brevern A.G. & Camproux A.C. Structural study of Outer Membrane Proteins using structural alphabet, Septièmes Journées Ouvertes de Biologie, Informatique et Mathématiques [JOBIM] (Bordeaux, 5-7 july 2006),

302.                        Mary Q. Yang, Jack Y. Yang, Craig W. Codrington. Identification of Transmembrane Proteins Using Variants of the Self-Organizing Feature Map Algorithm. In Knowledge discovery in bioinformatics : techniques, methods, and applications (Eds Xiaohua Hu, Yi Pan). 2006

303.                        Elofsson A, von Heijne G. Membrane Protein Structure: Prediction vs Reality. Annu Rev Biochem. 2007, 76: 125-140

304.                        Punta M, Forrest LR, Bigelow H, Kernytsky A, Liu J, Rost B. Membrane protein prediction methods. Methods. 2007; 41(4): 460-74.

305.                        Garrow AG, Westhead DR. A consensus algorithm to screen genomes for novel families of transmembrane beta barrel proteins. Proteins. 2007 Jun 7

306.                        Sapay N, LES PEPTIDES D’ANCRAGES A L’INTERFACE MEMBRANAIRE, PhD Thesis, UNIVERSITE CLAUDE BERNARD - LYON I, 2006

307.                        Albeau K, Analyse à grande échelle des textures des séquences protéiques via l’approche Hydrophobic Cluster Analysis (HCA). PhD Thesis, UNIVERSITE VERSAILLES SAINT-QUENTIN-EN-YVELINES, 2005

308.                        Wang Tao, Liu Chun-kit. Reverse vaccine analysis methods and vaccine development application. Progress in Microbiology and Immunology. 2006; 34 (1):.66-73 2006

309.                        Hye-Kyoung Jun, Hae-Ri Lee, Sung-Hoon Lee and Bong-Kyu Choi. Mapping of the proinflammatory domains of MspTL of Treponema lecithinolyticum. 2007. Microbiology 153(8): 2386-2392

310.                        Bigelow H, Rost B. Online tools for predicting integral membrane proteins. In: M Peirce & R Wait (Eds.): Proteomic analysis of membrane proteins: methods and protocols Humana, 2007, in press

311.                        Martin J, de Brevern AG, Camproux AC. In silico local structure approach: A case study on Outer Membrane Proteins. Proteins, 2007, in press

312.                        Gromiha MM, Yabuki Y, Suwa M. TMB Finding Pipeline: Novel Approach for Detecting beta-Barrel Membrane Proteins in Genomic Sequences. J Chem Inf Model. 2007, in press

313.                        Randall A, Cheng J, Sweredoski M, Baldi P. TMBpro: Secondary Structure, beta-contact, and Tertiary Structure Prediction of Transmembrane beta-Barrel Proteins. Bioinformatics. 2007

314.                        Satu Jääskeläinen, Pentti Riikonen, Tapio Salakoski and Mauno Vihinen. Evaluation of Protein Hydropathy Scales. In 2007 IEEE International Conference on Bioinformatics and Biomedicine BIBM 2007, Nov 2007.

315.                        M.S. Gelfand, D. Rodionov, Comparative genomics and functional annotation of bacterial transporters, Physics of Life Reviews (2007), doi: 10.1016/j.plrev.2007.10.003

316.                        Yang JY, Yang MQ, Dunker AK, Deng Y, Huang X. Investigation of transmembrane proteins using a computational approach. BMC Genomics. 2008;9 Suppl 1:S7.

317.                        Viratyosin W, Ingsriswang S, Pacharawongsakda E, Palittapongarnpim P. Genome-wide subcellular localization of putative outer membrane and extracellular proteins in Leptospira interrogans serovar Lai genome using bioinformatics approaches. BMC Genomics. 2008 Apr 21;9:181.

318.                        Hu J, Yan C. A method for discovering transmembrane beta-barrel proteins in Gram-negative bacterial proteomes. Computational Biology and Chemistry 32 (4), pp. 298-301: 2008

319.                        Ursula Hinz, and Amos Bairoch. The Impact of 3D Structures on a Protein Knowledgebase: From Proteins to Systems. In STRUCTURAL PROTEOMICS (Eds) Joel L Sussman & Israel Silman, World Scientific Publishing Co, 2008

320.                        Gromiha MM, Ahmad S. Suwa M. Neural network based prediction of protein structure and function: Comparison with other machine learning methods. 2008; Proceedings of the International Joint Conference on Neural Networks, art. no. 4634033, pp. 1739-1744

321.                        Peris P, López D, Campos M. IgTM: an algorithm to predict transmembrane domains and topology in proteins. BMC Bioinformatics. 2008 Sep 10;9:367

322.                        Díaz-Mejía JJ, Babu M, Emili A. Computational and experimental approaches to chart the Escherichia coli cell-envelope-associated proteome and interactome. FEMS Microbiol Rev. 2009; 33(1):66-97.

323.                        Song, H., Sandie, R., Wang, Y., Andrade-Navarro, M.A., Niederweis, M. Identification of outer membrane proteins of Mycobacterium tuberculosis 2008 Tuberculosis 88 (6), pp. 526-544

324.                        Vasilakos AV, Spyrou G Computational Intelligence in Medicine and Biology: A Survey  JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE 5 (12): 2365-2376 2008

325.                        M.L. Kalmokoff, J.W. Austinb, T.D. Cyrc, M.A. Heffordc, R.M. Teatherd and L.B. Selingere, Physical and genetic characterization of an outer-membrane protein (OmpM1) containing an N-terminal S-layer-like homology domain from the phylogenetically Gram-positive gut anaerobe Mitsuokella multacida. Anaerobe, 2009 in press

326.                        Kelm S, Shi J, Deane CM. iMembrane: homology-based membrane-insertion of proteins. Bioinformatics.;25(8):1086-8.

327.                        Remmert M, Linke D, Lupas AN, Soding J. HHomp-prediction and classification of outer membrane proteins NUCLEIC ACIDS RESEARCH 37: W446-W451 Suppl. S JUL 1 2009

328.                        Koehler, J., Mueller, R., Meiler, J. Improved prediction of trans-membrane spans in proteins using an artificial neural network  2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009 - Proceedings, art. no. 4925709, pp. 68-74

329.                        Fariselli P, Savojardo C, Martelli PL, Casadio R. Grammatical-Restrained Hidden Conditional Random Fields for Bioinformatics applications ALGORITHMS FOR MOLECULAR BIOLOGY 4: Art. No. 13 OCT 22 2009

330.                        Heinz E, Tischler P, Rattei T, Myers G, Wagner M, Horn M. Comprehensive in silico prediction and analysis of chlamydial outer membrane proteins reflects evolution and life style of the Chlamydiae. BMC Genomics. 2009; 10:634.

331.                        Ursula Hinz; From protein sequences to 3D-structures and beyond: the example of the UniProt knowledgebase. Cell Mol Life Sci. 2010;;67 (7):1049-64

332.                        Ou YY, Chen SA, Gromiha MM. Prediction of membrane spanning segments and topology in beta-barrel membrane proteins at better accuracy. J Comput Chem. 2010 Jan 15;31(1):217-23.

333.                        Piedachu Peris and Damián López. Transducer Inference by Assembling Specific Languages. Lecture Notes in Computer Science, 2010, Volume 6339/2010, 178-188, DOI: 10.1007/978-3-642-15488-1_15

334.                        Goudenège, D., Avner, S., Lucchetti-Miganeh, C., Barloy-Hubler, F. CoBaltDB: Complete bacterial and archaeal orfeomes subcellular localization database and associated resources. 2010 BMC Microbiology 10, art. no. 88

335.                        Zou L, Wang Z, Wang Y, Hu F. Combined prediction of transmembrane topology and signal peptide of beta-barrel proteins: using a hidden Markov model and genetic algorithms. Comput Biol Med. 2010 Jul;40(7):621-8. Epub 2010 May 21.

336.                        Tusnady GE, Simon I. Shedding light on transmembrane topology. In: Introduction to Protein Structure prediction, Huzefa Rangwala, George Karypis (Eds). 2010

337.                        Cox DL, Luthra A, Dunham-Ems S, Desrosiers DC, Salazar JC, Caimano MJ, Radolf JD. Surface immunolabeling and consensus computational framework to identify candidate rare outer membrane proteins of Treponema pallidum. Infect Immun. 2010 Sep 27. [Epub ahead of print]

338.                        Tusnady GE, Simon I. Shedding light on transmembrane topology. In: Introduction to Protein Structure prediction, Huzefa Rangwala, George Karypis (Eds). 2010

339.                        Satu Jaaskelainen, Pentti Riikonen, Tapio Salakoski, Mauno Vihinen. Accuracy of protein hydropathy predictions. International Journal of Data Mining and Bioinformatics. Volume 4, Number 6 / 2010, pp 735 - 754   

Elefsinioti AL, Bagos PG, Spyropoulos IC, Hamodrakas SJ. A database for G Proteins and their interaction with GPCRs.  BMC Bioinformatics, 2004, 5:208. (Impact Factor: 3.781, citations: 19)

340.                        Guo Y, Li M, Lu M, Wen Z, Huang Z. Predicting G-protein coupled receptors-G-protein coupling specificity based on autocross-covariance transform. Proteins. 2006; 65(1): 55-60.

341.                        Ono T, Hishigaki H. Prediction of GPCR-G Protein Coupling Specificity Using Features of Sequences and Biological Functions. Genomics, Proteomics and Bioinformatics. 2006. 4 (4), 238-244

342.                        Jiang Z, Guan C, Zhou Y. Computational prediction of the coupling specificity of g protein-coupled receptors. Appl Biochem Biotechnol. 2007;141 (1):109-18.

343.                        Fang YC, Sun WH, Wu LC, Huang HD, Juan HF, Horng JT. RINGdb: an integrated database for G protein-coupled receptors and regulators of G protein signaling.  BMC Genomics. 2006; 7:317.

344.                        Ganga D. Ghimire, Kenichiro Imai, Fumitsugu Akazawa, Toshiyuki Tsuji, Masashi Sonoyama and Shigeki Mitaku. Physicochemical properties of amino acid sequences of G-proteins for understanding GPCR-G-protein coupling. 2006; Chem-Bio Informatics Journal: 6(1) 1-16

345.                        Guan CP, Jiang ZR, Zhou YH. Predicting the coupling specificity of GPCRs to G-proteins by support vector machines. Genomics Proteomics Bioinformatics. 2005; 3(4): 247-51

346.                        Fanelli F, De Benedetti PG. Computational modeling approaches to structure-function analysis of G protein-coupled receptors. Chem Rev. 2005; 105(9): 3297-351

347.                        Jacques Haiech, Jean-Luc Galzi, Marie-Claude Kilhoffer, Marcel Hibert, Didier Rognan. Why G Protein-coupled Receptors Databases are Needed. In Raimund Mannhold, Hugo Kubinyi, Gerd Folkers (Eds).  Ligand Design for G Protein-coupled Receptors. 2006 Wiley, 2; 27-38

348.                        Ebbs ML, Amrein H. Taste and pheromone perception in the fruit fly Drosophila melanogaster. Pflugers Arch. 2007;454(5):735-47

349.                        Suga H, Haga T. Ligand screening system using fusion proteins of G protein-coupled receptors with G protein α subunits. Neurochemistry International 2007, 51 (2-4 SPEC. ISS.): 140-164

350.                        Yu-Ching Fang. An Integrated Database for G-Protein Coupled Receptors and Regulators of G-Protein Signaling. PhD Thesis, 2007, Institute of Life Science, National Central University, Taiwan

351.                        Shimamura T, Hiraki K, Takahashi N, Hori T, Ago H, Masuda K, Takio K, Ishiguro M, Miyano M. Crystal structure of squid rhodopsin with intracellularly extended cytoplasmic region.  JOURNAL OF BIOLOGICAL CHEMISTRY 283 (26): 17753-17756 JUN 27 2008

352.                        Gookin TE, Kim J, Assmann SM. Whole proteome identification of plant candidate G-protein coupled receptors in Arabidopsis, rice, and poplar: computational prediction and in-vivo protein coupling. Genome Biol. 2008;9(7):R120

353.                        Jain P, Wadhwa P, Aygun R, Podila G. Vector-G: multi-modular SVM-based heterotrimeric G protein prediction. In Silico Biol. 2008;8(2):141-55.

354.                        Ferrante M, Blackwell KT, Migliore M, Ascoli GA. Computational Models of Neuronal Biophysics and the Characterization of Potential Neuropharmacological Targets CURRENT MEDICINAL CHEMISTRY 15 (24): 2456-2471 2008

355.                        Strauss LG, Hoffend J, Koczan D, Pan L, Haberkorn U, Dimitrakopoulou-Strauss A Early effects of FOLFOX treatment of colorectal tumour in an animal model: assessment of changes in gene expression and FDG kinetics  EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING 36 (8): 1226-1234 AUG 2009

356.                        Gu, Q., Ding, Y.-S. Improved logitboost classifier based prediction of GPCR-G-Protein coupling with self-adaptive immune algorithm 2010, 4th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2010 , art. no. 5514858

357.                        M. Wachira, James. Sequence and Structural Elements in the Mechanism of Function of Rhodopsin-Like Family of G Protein-Coupled-Receptors Recent Patents on Endocrine, Metabolic & Immune Drug Discovery, Volume 4, Number 3, November 2010 , pp. 219-229(11)

358.                        Suen JY, Gardiner B, Grimmond S, Fairlie DP (2010) Profiling Gene Expression Induced by Protease-Activated Receptor 2 (PAR2) Activation in Human Kidney Cells. PLoS ONE 5(11): e13809. doi:10.1371/journal.pone.0013809

Bagos PG, Liakopoulos TD, Promponas VJ, Hamodrakas SJ. Topology prediction of β-barrel outer membrane proteins.  PINSA-B, 2005, Β71 (1): 19-41. (Impact Factor: -, citations: 1)

359.                        Mirus O, Schleiff E. Prediction of beta-barrel membrane proteins by searching for restricted domains. BMC Bioinformatics 2005, 6:254

Bagos PG, Liakopoulos TD, Hamodrakas SJ. Finding beta-barrel outer membrane proteins with a Markov chain model.  WSEAS Transactions on Biology and Biomedicine, 2004, 2(1) 186-189. (Impact Factor: -, citations: 8)

360.                        Moslavac S, Mirus O, Bredemeier R, Soll J, von Haeseler AP, Schleiff E. Conserved pore-forming regions in polypeptide-transporting proteins. FEBS Journal. 2005, 272(6): 1367-78.

361.                        Moslavac S, Bredemeier R, Mirus O, Granvogl B, Eichacker LA, Schleiff E. Proteomic analysis of the Outer Membrane of Anabaena sp. Strain PCC 7120. Journal of Proteome Research, 2005, 4(4): 1330-8.

362.                        Mirus O, Schleiff E. Prediction of beta-barrel membrane proteins by searching for restricted domains. BMC Bioinformatics 2005, 6:254

363.                        Moslavac S, Reisinger V, Berg M, Mirus O, Voskya O, Plocher M, Flores E, Eichaker LA, Schleiff E. The proteome of the heterocyst cell wall in Anabaena sp. PCC 7120. Biol Chem,2007  in press

364.                        Sunčana Moslavac. Outer membrane proteins of Anabaena sp. strain PCC 7120. 2007, PhD Thesis, Ludwig-Maximilians-Universität München.

365.                        Mubark RI, Keshk HA, Eladawy MI. Different Species and Proteins Classifiers and Protein's Structure Predictors Systems. INTERNATIONAL JOURNAL OF BIOLOGY AND BIOMEDICAL ENGINEERING. 2008, 4(2): 119-128

366.                        Goudenège, D., Avner, S., Lucchetti-Miganeh, C., Barloy-Hubler, F. CoBaltDB: Complete bacterial and archaeal orfeomes subcellular localization database and associated resources. 2010 BMC Microbiology 10, art. no. 88

367.                        Heinz E, Tischler P, Rattei T, Myers G, Wagner M, Horn M. Comprehensive in silico prediction and analysis of chlamydial outer membrane proteins reflects evolution and life style of the Chlamydiae. BMC Genomics. 2009; 10:634.

Spyropoulos IC, Liakopoulos TD, Bagos PG, Hamodrakas SJ. TMRPres2D - High quality depictions of transmembrane protein subunits. Bioinformatics, 2004, 20(17) 3258-3260. (Impact Factor: 4.328, citations: 19)

368.                        de Brevern AG, Wong H, Tournamille C, Colin Y, Le Van Kim C, Etchebest C. A structural model of a seven-transmembrane helix receptor: the Duffy antigen/receptor for chemokine (DARC). Biochim Biophys Acta. 2005; 1724(3): 288-306.

369.                        Cho, S.-H., Beckwith, J. Mutations of the Membrane-Bound Disulfide Reductase DsbD That Block Electron Transfer Steps from Cytoplasm to Periplasm in Escherichia coli.  J. Bacteriol. 2006 188: 5066-5076

370.                        Stapleton M, Carlson JW, Celniker SE. RNA editing in Drosophila melanogaster: New targets and functional consequences. RNA. 2006; 12 (11): 1922-1932

371.                        Srikar Chamala, Wesley A. Beckstead, Mark J. Rowe, David McClellan. Evolutionary selective pressure on three mitochondrial SNPs is consistent with their influence on metabolic efficiency in Pima Indians. Proceedings of Biotechnology and Bioinformatics Symposium (BIOT-2006)

372.                        Tschantz WR, Pfeifer ND, Meade CL, Wang L, Lanzetti A, Kamath AV, Berlioz-Seux F, Hashim MF. Expression, purification and characterization of the human membrane transporter protein OATP2B1 from Sf9 insect cells. Protein Expr Purif. 2007, in press

373.                        Battaglino RA, Pham L, Morse LR, Vokes M, Sharma A, Odgren PR, Yang M, Sasaki H, Stashenko P. NHA-oc/NHA2: A mitochondrial cation-proton antiporter selectively expressed in osteoclasts. Bone. 2007

374.                        W. Kus JV, Kelly J, Tessier L, Harvey H, Cvitkovitch DG, Burrows LL. Modification of Pseudomonas aeruginosa Pa5196 type IV Pilins at multiple sites with D-Araf by a novel GT-C family Arabinosyltransferase, Tfp  J Bacteriol. 2008;190(22):7464-78.

375.                        Benjamin Rietschel, Tabiwang N. Arrey, Bjoern Meyer, Sandra Bornemann, Malte Schuerken1, Michael Karas, and Ansgar Poetsch Elastase digests: New ammunition for shotgun membrane proteomics Molecular & Cellular Proteomics, 2008

376.                        Matthew Feldhammer, Stéphanie Durand Lenka Mrázová, Renée-Myriam Boucher, Rachel Laframboise, Robert Steinfeld, James E. Wraith, Helen Michelakakis, Otto P. van Diggelen, Martin Høebíèek, Stanislav Kmoch, Alexey V. Pshezhetsky. Sanfilippo syndrome type C: mutation spectrum in the heparan sulfate acetyl-CoA: -glucosaminide N-acetyltransferase (HGSNAT) gene. Human Mutation, 2009, in press

377.                        Peng Zhou and Zhicai Shang. 2D molecular graphics: a flattened world of chemistry and biology. Briefings in Bioinformatics, doi:10.1093/bib/bbp013

378.                        Dean S, Marchetti R, Kirk K, Matthews KR. A surface transporter family conveys the trypanosome differentiation signal. Nature. 2009;459(7244):213-7.

379.                        Rietschel B, Arrey TN, Meyer B, Bornemann S, Schuerken M, Karas M, Poetsch A Elastase digests: new ammunition for shotgun membrane proteomics Mol Cell Proteomics. 2009;8(5):1029-43.

380.                        Hu X. Structure Prediction of Membrane Proteins. In: Computational Methods for Protein Structure Prediction and Modeling Volume 2: Structure Prediction. Xu, Ying; Xu, Dong; Liang, Jie (Eds.). 2007, Springer.

381.                        Matthew Feldhammer, Stéphanie Durand and Alexey V. Pshezhetsky. Protein Misfolding as an Underlying Molecular Defect in Mucopolysaccharidosis III Type C. PLoS One. 2009; 4(10): e7434.

382.                        Miao, W.-G., Song, C.-F., Wang, Y., Wang, J.-S. HpaXm from Xanthomonas citri subsp. malvacearum is a novel harpin with two heptads for hypersensitive response               2010, Journal of Microbiology and Biotechnology 20 (1), pp. 1-9

383.                        Allen AM, Lexer CL, Hiscock SJ. Characterisation of sunflower-21 (SF21) genes expressed in pollen and pistil of Senecio squalidus (Asteraceae) and their relationship with other members of the SF21 gene family. Sexual Plant Reproduction. 2010

384.                        Nichols AS, Luetje CW.Transmembrane segment 3 of Drosophila melanogaster odorant receptor subunit 85b contributes to ligand-receptor interactions. J Biol Chem. 2010;285(16):11854-62.

385.                        Sangari FJ, Cayón AM, Seoane A, García-Lobo JM. Brucella abortus ure2 region contains an acid-activated urea transporter and a nickel transport system. BMC Microbiol. 2010;10:107.

386.                        Xu F, Zeng X, Haigh RD, Ketley JM, Lin J.  Identification and characterization of a new ferric enterobactin receptor, CfrB, in Campylobacter. J Bacteriol. 2010 Sep;192(17):4425-35. Epub 2010 Jun 28.

Papasaikas PK, Bagos PG, Litou ZI, Promponas VJ, Hamodrakas SJ. PRED-GPCR: GPCR recognition and family classification server. Nucleic Acids Res, 2004, 32(Web Server Issue):W380-382. (Impact Factor: 6.878, citations: 28)

387.                        Lu F, Li J, Jiang Z. Computational identification and analysis of G protein-coupled receptor targets. Drug Development Research. 67(10): 771 – 780

388.                        Fang YC, Sun WH, Wu LC, Huang HD, Juan HF, Horng JT. RINGdb: an integrated database for G protein-coupled receptors and regulators of G protein signaling.  BMC Genomics. 2006; 7:317.

389.                        Jacques Haiech, Jean-Luc Galzi, Marie-Claude Kilhoffer, Marcel Hibert, Didier Rognan. Why G Protein-coupled Receptors Databases are Needed. In Raimund Mannhold, Hugo Kubinyi, Gerd Folkers (Eds).  Ligand Design for G Protein-coupled Receptors. 2006 Wiley, 2; 27-38

390.                        Jiang Z, Guan C, Zhou Y. Computational prediction of the coupling specificity of g protein-coupled receptors. Appl Biochem Biotechnol. 2007;141 (1):109-18.

391.                        Guo YZ, Li M, Lu M, Wen Z, Wang K, Li G, Wu J. Classifying G protein-coupled receptors and nuclear receptors on the basis of protein power spectrum from fast Fourier transform. Amino Acids. 2006; 30(4): 397-402.

392.                        Guo YZ, Li ML, Wang KL, Wen ZN, Lu MC, Liu LX, Jiang L. Fast fourier transform-based support vector machine for prediction of G-protein coupled receptor subfamilies. Acta Biochim Biophys Sin (Shanghai). 2005; 37(11): 759-66

393.                        Choudhari Α, Gangadhar S, Agarwal S. HCRPDB: A Repository and Mining Tool for the Human Cell Receptor Protein families. International Conference on Informatika Systems Sciences and Engineering, Turkey, 2005

394.                        Gao QB, Wang ZZ. Classification of G-protein coupled receptors at four levels. Protein Eng Des Sel. 2006, 19(11):511-516

395.                        Greasley PJ, Jansen FP. G-protein-coupled receptor screening technologies. Drug Discovery Today: Technologies. 2005; 2 (2): 163-170

396.                        Punta M, Forrest LR, Bigelow H, Kernytsky A, Liu J, Rost B. Membrane protein prediction methods. Methods. 2007; 41(4): 460-74.

397.                        Fayyaz M, Khan A, Mujahid A, Kavokin A. Using multi level nearest neighbor classifiers for g-protein coupled receptor sub-families prediction. Lecture Notes in Computer Science 2007, 4463 LNBI, 564-576.

398.                        Davies MN, Gloriam DE, Secker A, Freitas AA, Mendao M, Timmis J, Flower DR. Proteomic applications of automated GPCR classification. Proteomics. 2007;7(16):2800-14

399.                        Davies MN, Secker A, Freitas AA, Mendao M, Timmis J, Flower DR. On the hierarchical classification of G Protein-Coupled Receptors. Bioinformatics, 2007, in press

400.                        Yu-Ching Fang. An Integrated Database for G-Protein Coupled Receptors and Regulators of G-Protein Signaling. PhD Thesis, 2007, Institute of Life Science, National Central University, Taiwan

401.                        Fayyaz, Mudassir    Mujahid, Adnan    Khan, Asifullah    Choi, Tae-Sun    Iqbal, Nadeem. G-protein Coupled Receptor Subfamilies Prediction Based on Nearest Neighbor Approach. Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering,. BIBE 2007: 1348-1354

402.                        Juan Carlos Mobarec‌, Marta Filizola. Advances in the development and application of computational methodologies for structural modeling of G-protein-coupled receptors. Expert Opinion on Drug Discovery 2008, 3(3): 343-35

403.                        Khan A, Khan MF, Choi TS. Proximity based GPCRs prediction in transform domain. Biochem Biophys Res Commun. 2008; 371(3):411-5.

404.                        Gupta, R., Mittal, A., Singh, K. A novel and efficient technique for identification and classification of GPCRs. IEEE Transactions on Information Technology in Biomedicine 12 (4), pp. 541-548: 2008

405.                        Gao QB, Wu C, Ma XQ, Lu J, He J. Classification of amine type G-protein coupled receptors with feature selection. Protein Pept Lett. 2008;15(8):834-42.

406.                        Gookin TE, Kim J, Assmann SM. Whole proteome identification of plant candidate G-protein coupled receptors in Arabidopsis, rice, and poplar: computational prediction and in-vivo protein coupling. Genome Biol. 2008;9(7):R120.

407.                        Davies, M.N., Secker, A., Freitas, A.A., Timmis, J., Clark, E., Flower, D.R. Alignment-independent techniques for protein classification  2008 Current Proteomics 5 (4), pp. 217-223

408.                         Michalke K, Gravière ME, Huyghe C, Vincentelli R, Wagner R, Pattus F, Schroeder K, Oschmann J, Rudolph R, Cambillau C, Desmyter A. Mammalian G-protein-coupled receptor expression in Escherichia coli: I. High-throughput large-scale production as inclusion bodies. Anal Biochem. 2009;386(2):147-55.

409.                        Matthew N Davies, Andrew Secker, Mark Halling-Brown, David S Moss, Alex A Freitas, Jon Timmis, Edward Clark and Darren R Flower. GPCRTree: online hierarchical classification of GPCR function. BMC Research Notes 2008, 1:67

410.                        .Qiu JD, Huang JH, Liang RP, Lu XQ.  Prediction of G-protein-coupled receptor classes based on the concept of Chou's pseudo amino acid composition: an approach from discrete wavelet transform. Anal Biochem. 2009, 1;390(1):68-73

411.                        Li Z, Zhou X, Dai Z, Zou X. Classification of G-protein coupled receptors based on support vector machine with maximum relevance minimum redundancy and genetic algorithm. BMC Bioinformatics. 2010 Jun 16;11:325

412.                        Moriyama EN, Opiyo SO. Bioinformatics of Seven-Transmembrane Receptors in Plant Genomes. In Yalovsky S, Baluska F, Jones A (Eds) Integrated G Proteins Signaling in Plants. pp 251-277

413.                        Cobanoglu, M.C.;   Sezerman, U.;   Karabulut, N.P. Determinig the ligand-specific regions of peptide-binding G-Protein Coupled Receptors. 5th International Symposium on Health Informatics and Bioinformatics (HIBIT), 2010 20-22 April 2010

414.                        Tannu Kumari, Bhaskar Pant and K. R. Pardasani A SVM Model for AAC Based Classification of Class B GPCRs 6th World Congress of Biomechanics (WCB 2010). August 1-6, 2010 Singapore, IFMBE Proceedings, 2010, Volume 31, Part 6, 1607-1610, DOI: 10.1007/978-3-642-14515-5_409

Bagos PG, Liakopoulos TD, Spyropoulos IC, Hamodrakas SJ. PRED-TMBB: A web server for predicting the topology of β-barrel outer membrane proteins. Nucleic Acids Res, 2004, 32(Web Server Issue). W400-404. (Impact Factor:  6.878, citations: 81)

415.                        Fariselli P, Martelli PL, Casadio R. A new decoding algorithm for hidden Markov models improves the prediction of the topology of all-beta membrane proteins. BMC Bioinformatics 2005, 6(Suppl 4):S12

416.                        Garrow AG, Agnew A, Westhead DR.  TMB-Hunt: An amino acid composition based method to screen proteomes for beta-barrel transmembrane proteins. BMC Bioinformatics 2005, 6:56

417.                        Gromiha MM, Suwa M. A simple statistical method for discriminating outer membrane proteins with better accuracy. Bioinformatics 2005; 21(7):961-968.

418.                        Moslavac S, Mirus O, Bredemeier R, Soll J, von Haeseler AP, Schleiff E. Conserved pore-forming regions in polypeptide-transporting proteins. FEBS Journal. 2005, 272(6): 1367-78.

419.                        Sobolev BN, Olenina LV, Kolesanova EF, Poroikov VV, Archakov AI. Computer Design of Vaccines: Approaches, Software Tools and Informational Resources. Current Computer - Aided Drug Design, 2005, 1(2): 207-222

420.                        Humphries AD, Streimann IC, Stojanovski D, Johnston AJ, Yano M, Hoogenraad NJ, Ryan MT. Dissection of the mitochondrial import and assembly pathway for human Tom40. J Biol Chem. 2005, 280(12): 11535-11543

421.                        Thundimadathil J, Roeske RW, Guo L  A synthetic peptide forms voltage-gated porin-like ion channels in lipid bilayer membranes. Biochem Biophys Res Commun. 2005; 330(2): 585-590

422.                        Thundimadathil J, Roeske RW, Jiang HY, Guo LL. Aggregation and porin-like channel activity of a beta sheet peptide.  Biochemistry 2005; 44 (30): 10259-10270

423.                        Garrow AG, Agnew A, Westhead DR. TMB-Hunt: a web server to screen sequence sets for transmembrane ß-barrel proteins. Nucleic Acids Research 2005 33(Web Server issue):W188-W192

424.                        Gromiha MM, Ahmad S. Suwa M. TMBETA-NET: discrimination and prediction of membrane spanning ß-strands in outer membrane proteins. Nucleic Acids Research 2005 33(Web Server issue):W164-W167

425.                        Letoffe S, Wecker K, Delepierre M, Delepelaire P, Wandersman C. Activities of the Serratia marcescens heme receptor HasR and isolated plug and beta-barrel domains: the beta-barrel forms a heme-specific channel. J Bacteriol. 2005;187(13):4637-45.

426.                        Bendtsen JD, Binnewies TT, Hallin PF, Ussery DW. Genome update: prediction of membrane proteins in prokaryotic genomes. Microbiology. 2005; 151(Pt 7):2119-21.

427.                        Desvaux M, Khan A, Beatson SA, Scott-Tucker A, Henderson IR. Protein secretion systems in Fusobacterium nucleatum: genomic identification of Type 4 piliation and complete Type V pathways brings new insight into mechanisms of pathogenesis. Biochim Biophys Acta. 2005; 1713 (2): 92-112

428.                        Gentle IE, Burri L, Lithgow T. Molecular architecture and function of the Omp85 family of proteins. Molecular Microbiology 2005, 58 (5): 1216–1225

429.                        Aivaliotis M, Haase W, Karas M, Tsiotis G. Proteomic analysis of chlorosome-depleted membranes of the green sulfur bacterium Chlorobium tepidum. Proteomics. 2005; 6(1): 217-232

430.                        Berven FS, Karlsen OA, Straume AH, Flikka K, Murrell JC, Fjellbirkeland A, Lillehaug JR, Eidhammer I, Jensen HB. Analysing the outer membrane subproteome of Methylococcus capsulatus (Bath) using proteomics and novel biocomputing tools. Arch Microbiol. 2006; 184(6): 362-77.

431.                        Runke G, Maier E, Summers WA, Bay DC, Benz R, Court DA. Deletion variants of Neurospora mitochondrial porin: Electrophysiological and spectroscopic analysis. Biophys J. 2006; 90:3155-3164.

432.                        Marani P, Wagner S, Baars L, Genevaux P, De Gier JW, Nilsson I, Casadio R, von Heijne G. New Escherichia coli outer membrane proteins identified through prediction and experimental verification. Protein Science. 2006, 15(4):884-9

433.                        Forrest LR, Tang CL, Honig B. On the accuracy of homology modeling and sequence alignment methods applied to membrane proteins. Biophys J. 2006 91(2):508-17.

434.                        Pajon R, Yero D, Lage A, Llanes A, Borroto CJ. Computational identification of beta-barrel outer-membrane proteins in Mycobacterium tuberculosis predicted proteomes as putative vaccine candidates. Tuberculosis 86 (3-4): 290-302; 2006

435.                        Lee JW, Lee SY, Song H, Yoo JS. The proteome of Mannheimia succiniciproducens, a capnophilic rumen bacterium. Proteomics. 2006; 6(12): 3550-3566.

436.                        Marczak M, Mazur A, Krol JE, Gruszecki WI, Skorupska A. Lipoprotein PssN of Rhizobium leguminosarum bv. trifolii: Subcellular Localization and Possible Involvement in Exopolysaccharide Export. J Bacteriol. 2006; 188(19):6943-52.

437.                        Louvel H, Bommezzadri S, Zidane N, Boursaux-Eude C,  Creno S, Magnier A, Rouy Z,  Medigue C,  Girons IS, Bouchier C, Picardeau M. Comparative and functional genomic analyses of iron transport and regulation in Leptospira spp. J Bacteriol. 2006; 188 (22): 7893-7904

438.                        Forman S, Bobrov, AG, Kirillina O, Craig SK, Abney J, Fetherston JD, Perry RD. Identification of critical amino acid residues in the plague biofilm Hms proteins. Microbiology, 2006; 152 (11):3399-3410 

439.                        Sadovskaya NS, Sutormin RA, Gelfand MS. Recognition of transmembrane segments in proteins: Review and consistency-based benchmarking of internet servers. 2006; Journal of Bioinformatics and Computational Biology 4 (5): 1033-1056

440.                        Elofsson A, von Heijne G. Membrane Protein Structure: Prediction vs Reality. Annu Rev Biochem. 2007, 76: 125-140

441.                        Punta M, Forrest LR, Bigelow H, Kernytsky A, Liu J, Rost B. Membrane protein prediction methods. Methods. 2007; 41(4): 460-74.

442.                        Aivaliotis M, Karas M, Tsiotis G. An alternative strategy for the membrane proteome analysis of the green sulfur bacterium Chlorobium tepidum using blue native PAGE and 2-D PAGE on purified membranes. J Proteome Res. 2007; 6(3):1048-58

443.                        Dautin N, Barnard TJ, Anderson DE, Bernstein HD. Cleavage of a bacterial autotransporter by an evolutionarily convergent autocatalytic mechanism. EMBO J. 2007, 26 (7): 1942-1952

444.                        Wally J, Buchanan SK. A structural comparison of human serum transferrin and human lactoferrin.2007, BioMetals. 20 (3-4): 249-262

445.                        Ge Y, Rikihisa Y. Surface-exposed Proteins of Ehrlichia chaffeensis. Infect Immun. 2007 in press

446.                        Sijbrandi R, MOLECULAR INSIGHT INTO THE PATHOGENIC SYNERGY BETWEEN E. COLI AND B. FRAGILIS IN SECONDARY PERITONITIS. PhD Thesis, Vrije Universiteit Amsterdam, 2007

447.                        Magalashvili L, Pechatnikov I, Wexler HM, Nitzan Y. Isolation and characterization of the Omp-PA porin from Porphyromonas asaccharolytica, determination of the omp-PA gene sequence and prediction of Omp-PA protein structure. Anaerobe. 2007;13(2):74-82

448.                        Madhavi K. Ganapathiraju. Application of Language Technologies in Biology: Feature Extraction and Modeling for Transmembrane Helix Prediction. PhD Thesis, Carnegie Mellon University, 2007

449.                        Sundaresh S, Randall A, Unal B, Petersen JM, Belisle JT, Hartley MG, Duffield M, Titball RW, Davies DH, Felgner PL, Baldi P. From protein microarrays to diagnostic antigen discovery: a study of the pathogen Francisella tularensis. 2007; Bioinformatics, 23(13):i508-18

450.                        Wedemeyer U, Peng G, Michel H, Hartung K. Protein AQ_1862 from the hyperthermophilic bacterium Aquifex aeolicus is a porin and contains two conductance pathways of different selectivity. Biophys J. 2007

451.                        Sunčana Moslavac. Outer membrane proteins of Anabaena sp. strain PCC 7120. 2007, PhD Thesis, Ludwig-Maximilians-Universität München.

452.                        Diao Y, Ma D, Wen Z, Yin J, Xiang J and M. Li. Using pseudo amino acid composition to predict transmembrane regions in protein: cellular automata and Lempel-Ziv complexity. Amino Acids. 2007,

453.                        Bigelow H, Rost B. Online tools for predicting integral membrane proteins. In: M Peirce & R Wait (Eds.): Proteomic analysis of membrane proteins: methods and protocols Humana, 2007, in press

454.                        Villoutreix BO, Renault N, Lagorce D, Sperandio O, Montes M, Miteva MA. Free resources to assist structure-based virtual ligand screening experiments. Curr Protein Pept Sci. 2007; 8 (4):381-411

455.                        Ge Y, Rikihisa Y. Identification of Novel Surface Proteins of Anaplasma phagocytophilum by Affinity Purification and Proteomics. 2007, Journal of Bacteriology, 189 (21): 7819-7828

456.                        Biswas S, Mohammad MM, Patel DR, Movileanu L, van den Berg B. Structural insight into OprD substrate specificity. Nat Struct Mol Biol. 2007 in press

457.                        Randall A, Cheng J, Sweredoski M, Baldi P. TMBpro: Secondary Structure, beta-contact, and Tertiary Structure Prediction of Transmembrane beta-Barrel Proteins. Bioinformatics. 2007

458.                        Zhang C, Xiong Q, Kikuchi T, Rikihisa Y. Identification of 19 Polymorphic Major Outer Membrane Protein Genes and Their Immunogenic Peptides in Ehrlichia ewingii for Use in a Serodiagnostic Assay. Clin Vaccine Immunol. 2007

459.                        Jeong JA, Ko KM, Park HS, Lee J, Jang C, Jeon CJ, Koh GY, Kim H. Membrane proteomic analysis of human mesenchymal stromal cells during adipogenesis. Proteomics. 2007; 7(22):4181-91.

460.                        Yan C, Hu J, Wang Y. Discrimination of outer membrane proteins with improved performance. BMC Bioinformatics. 2008; 9:47

461.                        G Y Liu, P Nie, J Zhang and N Li. Proteomic analysis of the sarcosine-insoluble outer membrane fraction of Flavobacterium columnare. Journal of Fish Diseases 2008

462.                        Lee SY, Kim JM, Song H, Lee JW, Kim TY, Jang YS. From genome sequence to integrated bioprocess for succinic acid production by Mannheimia succiniciproducens. Appl Microbiol Biotechnol. 2008;79(1):11-22.

463.                        Jeans C, Singer SW, Chan CS, Verberkmoes NC, Shah M, Hettich RL, Banfield JF, Thelen MP. Cytochrome 572 is a conspicuous membrane protein with iron oxidation activity purified directly from a natural acidophilic microbial community. ISME J. 2008; 2(5):542-50.

464.                        Hu J, Yan C. A method for discovering transmembrane beta-barrel proteins in Gram-negative bacterial proteomes. Computational Biology and Chemistry 32 (4), pp. 298-301: 2008

465.                        Ramakrishnan, G., Meeker, A., Dragulev, B  FslE is necessary for siderophore-mediated iron acquisition in Francisella tularensis Schu S4, Journal of Bacteriology 190 (15), pp. 5353-5361, 2008

466.                        Montgomerie S, Cruz JA, Shrivastava S, Arndt D, Berjanskii M, Wishart DS. PROTEUS2: a web server for comprehensive protein structure prediction and structure-based annotation. Nucleic Acids Res. 2008 Jul 1;36(Web Server issue):W202-9.

467.                        Díaz-Mejía JJ, Babu M, Emili A. Computational and experimental approaches to chart the Escherichia coli cell-envelope-associated proteome and interactome. FEMS Microbiol Rev. 2009; 33(1):66-97.

468.                        Brosig, A., Nesper, J., Boos, W., Welte, W., Diederichs, K. Crystal Structure of a Major Outer Membrane Protein from Thermus thermophilus HB27 2009 Journal of Molecular Biology 385 (5), pp. 1445-1455

469.                        Rembert Pieper, Shih-Ting Huang, Jeffrey M. Robinson, David J. Clark, Hamid Alami, Prashanth P. Parmar, Robert D. Perry, Robert D. Fleischmann and Scott N. Peterson. Temperature and growth phase influence the outer-membrane proteome and the expression of a type VI secretion system in Yersinia pestis Microbiology 155 (2009), 498-512

470.                        Pedro Celso Nogueira Teixeira, Cristina Alves Magalhães de Souza, Mônica Santos de Freitas, Débora Foguel, Ernesto Raul Caffarena and Luiz Anastacio Alves. Predictions Suggesting a Participation of β-Sheet Configuration in the M2 Domain of the P2X7 Receptor: A Novel Conformation? Biophysical Journal Volume 96, Issue 3, 4 February 2009, Pages 951-963

471.                        Remmert M, Linke D, Lupas AN, Soding J. HHomp-prediction and classification of outer membrane proteins NUCLEIC ACIDS RESEARCH 37: W446-W451 Suppl. S JUL 1 2009

472.                        Nugent, T., Jones, D.T. Transmembrane protein topology prediction using support vector machines 2009 BMC Bioinformatics 10, art. no. 159

473.                        Lin, M., Zhang, C., Gibson, K., Rikihisa, Y.                 Analysis of complete genome sequence of Neorickettsia risticii: Causative agent of Potomac horse fever 2009 Nucleic Acids Research 37 (18), pp. 6076-6091

474.                        Mullins, M.A., Register, K.B., Bayles, D.O., Loving, C.L., Nicholson, T.L., Brockmeier, S.L., Dyer, D.W., Phillips, G.J. Characterization and comparative analysis of the genes encoding Haemophilus parasuis outer membrane proteins P2 and P5  2009 Journal of Bacteriology 191 (19), pp. 5988-6002

475.                        Goulart, C.L., Lery, L.M.S., Diniz, M.M.P., Vianez-Junior, J.L., Neves-Ferreira, A.G.C., Perales, J., Bisch, P.M., Von Krüger, W.M.A. Molecular analysis of VCA1008: A putative phosphoporin of Vibrio cholerae 2009 FEMS Microbiology Letters 298 (2), pp. 241-248

476.                        Pinne, M., Haake, D.A. A comprehensive approach to identification of surface-exposed, outer membrane-spanning proteins of Leptospira interrogans 2009 PLoS ONE 4 (6), art. no. e6071

477.                        Heinz E, Tischler P, Rattei T, Myers G, Wagner M, Horn M. Comprehensive in silico prediction and analysis of chlamydial outer membrane proteins reflects evolution and life style of the Chlamydiae. BMC Genomics. 2009; 10:634.

478.                        Singha UK, Sharma S, Chaudhuri M. Downregulation of mitochondrial porin inhibits cell growth and alters respiratory phenotype in Trypanosoma brucei. Eukaryot Cell. 2009 Sep;8(9):1418-28. Epub 2009 Jul 17.

479.                        Jarosławski S, Duquesne K, Sturgis JN, Scheuring S. High-resolution architecture of the outer membrane of the Gram-negative bacteria Roseobacter denitrificans. Mol Microbiol. 2009 Dec;74(5):1211-22. Epub 2009 Oct 15.

480.                        Lin M, Zhang C, Gibson K, Rikihisa Y.Analysis of complete genome sequence of Neorickettsia risticii: causative agent of Potomac horse fever. Nucleic Acids Res. 2009 Oct;37(18):6076-91. Epub 2009 Aug 6.

481.                        Marin R, Díaz M, Alonso R, Sanz A, Arévalo MA, Garcia-Segura LM. Role of estrogen receptor alpha in membrane-initiated signaling in neural cells: interaction with IGF-1 receptor. J Steroid Biochem Mol Biol. 2009 Mar;114(1-2):2-7. Epub 2009 Jan 9.

482.                        Hsu SC, Inoue K. Two evolutionarily conserved essential beta-barrel proteins in the chloroplast outer envelope membrane. Biosci Trends. 2009 Oct;3(5):168-78. Review.

483.                        Remmert M, Biegert A, Linke D, Lupas AN, Söding J. Evolution of outer membrane beta-barrels from an ancestral beta beta hairpin. Mol Biol Evol. 2010 Jun;27(6):1348-58. Epub 2010 Jan 27.

484.                        Abu Khweek A, Fetherston JD, Perry RD. Analysis of HmsH and its role in plague biofilm formation. Microbiology. 2010 May;156(Pt 5):1424-38. Epub 2010 Jan 21.

485.                        Lenhart TR, Akins DR. Borrelia burgdorferi locus BB0795 encodes a BamA orthologue required for growth and efficient localization of outer membrane proteins. Mol Microbiol. 2010 Feb;75(3):692-709. Epub 2009 Dec 16.

486.                        Belchik SM, Schaeffer SM, Hasenoehrl S, Xun L. A beta-barrel outer membrane protein facilitates cellular uptake of polychlorophenols in Cupriavidus necator. Biodegradation. 2010 Jun;21(3):431-9. Epub 2009 Nov 24.

487.                        Pieper R, Huang ST, Parmar PP, Clark DJ, Alami H, Fleischmann RD, Perry RD, Peterson SN. Proteomic analysis of iron acquisition, metabolic and regulatory responses of Yersinia pestis to iron starvation. BMC Microbiol. 2010 Jan 29;10:30.

488.                        Ou YY, Chen SA, Gromiha MM. Prediction of membrane spanning segments and topology in beta-barrel membrane proteins at better accuracy. J Comput Chem. 2010 Jan 15;31(1):217-23.

489.                        Hay ID, Rehman ZU, Rehm BH. Membrane topology of outer membrane protein AlgE, which is required for alginate production in Pseudomonas aeruginosa. Appl Environ Microbiol. 2010 Mar;76(6):1806-12. Epub 2010 Jan 22.

490.                        Goudenège, D., Avner, S., Lucchetti-Miganeh, C., Barloy-Hubler, F. CoBaltDB: Complete bacterial and archaeal orfeomes subcellular localization database and associated resources. 2010 BMC Microbiology 10, art. no. 88

491.                        Baldo L, Desjardins CA, Russell JA, Stahlhut JK, Werren JH. Accelerated microevolution in an outer membrane protein (OMP) of the intracellular bacteria Wolbachia. BMC Evol Biol. 2010 Feb 17;10:48.

492.                        Cox DL, Luthra A, Dunham-Ems S, Desrosiers DC, Salazar JC, Caimano MJ, Radolf JD. Surface immunolabeling and consensus computational framework to identify candidate rare outer membrane proteins of Treponema pallidum. Infect Immun. 2010 Sep 27. [Epub ahead of print]

493.                        Kojima S, Ko KC, Takatsuka Y, Abe N, Kaneko J, Itoh Y, Kamio Y. Cadaverine Covalently-linked to the Peptidoglycan is Required for the Interaction Between the Peptidoglycan and Periplasm-exposed SLH Domain of Major Outer Membrane Protein Mep45 in Selenomonas ruminantium. J Bacteriol. 2010 Sep 17. [Epub ahead of print]

494.                        Sen B, Meeker A, Ramakrishnan G. The fslE homolog, FTL_0439 (fupA/B), mediates siderophore-dependent iron uptake in Francisella tularensis LVS. Infect Immun. 2010 Oct;78(10):4276-85. Epub 2010 Aug 9.

495.                        Shu-An Chen, Yu-Yen Ou and M. Michael Gromiha Topology Prediction of α-Helical and β-Barrel Transmembrane Proteins Using RBF Networks Lecture Notes in Computer Science, 2010, Volume 6215/2010, 642-649

Bagos PG, Liakopoulos TD, Spyropoulos IC, Hamodrakas SJ. A Hidden Markov Model capable of predicting and discriminating β-barrel outer membrane proteins. BMC Bioinformatics, 2004, 5:29. (Impact Factor:  3.781, citations: 63)

496.                        A.V.S.K. Mohan Katta, Rajeshwari Marikkannu, Rajiv V. Basaiawmoit, Sankaran Krishnaswamy Consensus based validation of membrane porins. In Silico Biology 2004, 4 (0046)

497.                        Henderson NS, Shu Kin So S, Martin C, Kulkarni R, Thanassi DG. Topology of the outer membrane usher PapC determined by site-directed fluorescence labeling. J Biol Chem. 2004; 279(51):53747-54

498.                        Garrow AG, Agnew A, Westhead DR.  TMB-Hunt: An amino acid composition based method to screen proteomes for beta-barrel transmembrane proteins. BMC Bioinformatics 2005, 6:56

499.                        Gromiha MM, Suwa M. A simple statistical method for discriminating outer membrane proteins with better accuracy. Bioinformatics 2005; 21(7):961-968.

500.                        Choo KH, Tong JC, Zhang L. Recent applications of hidden markov models in computational biology. Genomics Proteomics Bioinformatics. 2004; 2(2):84-96.

501.                        Igo MM, Walker A, Kirkpatrick B, Bisson L. The Xylella fastidiosa cell surface. The 2004 Pierce's Disease Research Symposium, December 7 - 10, 2004, San Diego, California.

502.                        Moslavac S, Mirus O, Bredemeier R, Soll J, von Haeseler AP, Schleiff E. Conserved pore-forming regions in polypeptide-transporting proteins. FEBS Journal. 2005, 272(6): 1367-78.

503.                        Rey S, Acab M, Gardy JL, Laird MR, deFays K, Lambert C, Brinkman FS. PSORTdb: a protein subcellular localization database for bacteria. Nucleic Acids Res. 2005; 33 Database Issue: D164-8

504.                        Moslavac S, Bredemeier R, Mirus O, Granvogl B, Eichacker LA, Schleiff E. Proteomic analysis of the Outer Membrane of Anabaena sp. Strain PCC 7120. Journal of Proteome Research, 2005, 4(4): 1330-8.

505.                        Gromiha MM, Ahmad S. Suwa M. Application of residue distribution along the sequence for discriminating outer membrane proteins.  Computational Biology and Chemistry, 2005; 29(2): 135-142

506.                        Mussi MA, Limansky AS, Viale AM Acquisition of resistance to carbapenems in multidrug-resistant clinical strains of Acinetobacter baumannii: Natural Insertional inactivation of a gene encoding a member of a novel family of beta-barrel outer membrane proteins. Antimicrobial agents and chemotherapy, 2005, 49(4): 1432-1440

507.                        Gromiha MM.  Motifs in outer membrane protein sequences: Applications for discrimination. Biophys Chem. 2005, 117(1):65-71.

508.                        Garrow AG, Agnew A, Westhead DR. TMB-Hunt: a web server to screen sequence sets for transmembrane ß-barrel proteins. Nucleic Acids Research 2005 33(Web Server issue):W188-W192

509.                        Gromiha MM, Ahmad S. Suwa M. TMBETA-NET: discrimination and prediction of membrane spanning ß-strands in outer membrane proteins. Nucleic Acids Research 2005 33(Web Server issue):W164-W167

510.                        Desvaux M, Khan A, Beatson SA, Scott-Tucker A, Henderson IR. Protein secretion systems in Fusobacterium nucleatum: genomic identification of Type 4 piliation and complete Type V pathways brings new insight into mechanisms of pathogenesis. Biochim Biophys Acta. 2005; 1713 (2): 92-112

511.                        Lazaridis T. Structural Determinants of Transmembrane b-barrels. J Chem Theory Comput. 2005 1(4): 716-722

512.                        Park KJ, Gromiha MM, Horton P, Suwa M. Discrimination of outer membrane proteins using support vector machines. Bioinformatics. 2005 21(23):4223-9

513.                        Mirus O, Schleiff E. Prediction of beta-barrel membrane proteins by searching for restricted domains. BMC Bioinformatics 2005, 6:254

514.                        Ssu-Hua Huang, Ru-Sheng Liu, Chien-Yu Chen, Ya-Ting Chao, Shu-Yuan Chen. Prediction of Outer Membrane Proteins by Support Vector Machines Using Combinations of Gapped Amino Acid Pair Compositions. Fifth IEEE Symposium on Bioinformatics and Bioengineering (BIBE'05) pp. 113-120.

515.                        Berven FS, Karlsen OA, Straume AH, Flikka K, Murrell JC, Fjellbirkeland A, Lillehaug JR, Eidhammer I, Jensen HB. Analysing the outer membrane subproteome of Methylococcus capsulatus (Bath) using proteomics and novel biocomputing tools. Arch Microbiol. 2006; 184(6): 362-77.

516.                        Gromiha MM, Suwa M. Discrimination of outer membrane proteins using machine learning algorithms. Proteins. 2006, 63(4):1031-7.

517.                        Yuan Z, Zhang F, Davis MJ, Boden M, Teasdale RD. Predicting the solvent accessibility of transmembrane residues from protein sequence. J Proteome Res. 2006; 5(5): 1063-70.

518.                        Bigelow H, Rost B. PROFtmb: a web server for predicting bacterial transmembrane beta barrel proteins. Nucleic Acids Res. 2006; 34(Web Server issue): W186-8.

519.                        Gromiha MM, Suwa M. Influence of amino acid properties for discriminating outer membrane proteins at better accuracy. Biochim Biophys Acta. 2006. 1764 (9), 1493-1497

520.                        Gromiha MM, Yabuki Y, Kundu S, Suharnan S, Suwa M. TMBETA-GENOME: database for annotated β-barrel membrane proteins in genomic sequences. Nucleic Acids Res. 2006, 35(Database issue):D314-6.

521.                        Zafer Aydin, Yucel Altunbasak, Bayesian Protein Secondary Structure Prediction with Near-Optimal Segmentations, IEEE Transactions on Signal Processing, 2007, 55 (7), Part 1: 3512-3525

522.                        Wu Z, Feng E, Wang Y, Chen L. Discrimination of outer membrane proteins by a new measure of information discrepancy. Protein and Peptide Letters 14 (1); 37-44

523.                        Jiao Y, Newman DK. The pio Operon Is Essential for Phototrophic Fe(II) Oxidation in Rhodopseudomonas palustris TIE-1. 2006, J Bacteriology; 189(5): 1765–1773

524.                        Punta M, Forrest LR, Bigelow H, Kernytsky A, Liu J, Rost B. Membrane protein prediction methods. Methods. 2007; 41(4): 460-74.

525.                        De Fonzo V, Aluffi-Pentini F, Parisi V. Hidden Markov Models in bioinformatics. Curr Bioinform 2007; 2(1): 49-61

526.                        Garrow AG, Westhead DR. A consensus algorithm to screen genomes for novel families of transmembrane beta barrel proteins. Proteins. 2007 Jun 7

527.                        Moslavac S, Reisinger V, Berg M, Mirus O, Voskya O, Plocher M, Flores E, Eichaker LA, Schleiff E. The proteome of the heterocyst cell wall in Anabaena sp. PCC 7120. Biol Chem, in press

528.                        Jiao Y, PHYSIOLOGICAL AND MECHANISTIC STUDIES OF PHOTOTROPHIC FE(II) OXIDATION IN PURPLE NON-SULFUR BACTERIA. PhD Thesis, California Institute of Technology, 2007

529.                        Sapay N, LES PEPTIDES D’ANCRAGES A L’INTERFACE MEMBRANAIRE, PhD Thesis, UNIVERSITE CLAUDE BERNARD - LYON I, 2006

530.                        Sunčana Moslavac. Outer membrane proteins of Anabaena sp. strain PCC 7120. 2007, PhD Thesis, Ludwig-Maximilians-Universität München.

531.                        Bigelow H, Rost B. Online tools for predicting integral membrane proteins. In: M Peirce & R Wait (Eds.): Proteomic analysis of membrane proteins: methods and protocols Humana, 2007, in press

532.                        Martin J, de Brevern AG, Camproux AC. In silico local structure approach: A case study on Outer Membrane Proteins. Proteins, 2007, in press

533.                        Zou, Lingyun    Wang, Zhengzhi. Predicting Transmembrane Topology of β-barrel Membrane Proteins with A Hidden Markov Model. The 1st International Conference on Bioinformatics and Biomedical Engineering, ICBBE 2007. pp: 145-148

534.                         Gromiha MM. Bioinformatics on β-Barrel Membrane Proteins: Sequence and Structural Analysis, Discrimination and Prediction. J.C. Rajapakse, B. Schmidt, and G. Volkert (Eds.): PRIB 2007, LNBI 4774, pp. 148–157, 2007. © Springer-Verlag Berlin Heidelberg 2007

535.                        Gromiha MM, Yabuki Y, Suwa M. TMB Finding Pipeline: Novel Approach for Detecting beta-Barrel Membrane Proteins in Genomic Sequences. J Chem Inf Model. 2007, in press

536.                        Randall A, Cheng J, Sweredoski M, Baldi P. TMBpro: Secondary Structure, beta-contact, and Tertiary Structure Prediction of Transmembrane beta-Barrel Proteins. Bioinformatics. 2007

537.                        Yan C, Hu J, Wang Y. Discrimination of outer membrane proteins with improved performance. BMC Bioinformatics. 2008; 9:47

538.                        Gromiha MM, Suwa M. Current developments on beta-barrel membrane proteins: sequence and structure analysis, discrimination and prediction. Curr Protein Pept Sci. 2007;8(6):580-99.

539.                        Yan, Changhui    Hu, Jing. A Hidden Markov Model Approach to Identifying HTH Motifs Using Protein Sequence and Predicted Solvent Accessibility. IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology, 2006. CIBCB '06. 2006

540.                        Lin H. The modified Mahalanobis Discriminant for predicting outer membrane proteins by using Chou's pseudo amino acid composition. J Theor Biol. 2008

541.                        Gromiha MM, Yabuki Y. Functional discrimination of membrane proteins using machine learning techniques. BMC Bioinformatics. 2008;9:135

542.                        Ou YY, Gromiha MM, Chen SA, Suwa M. TMBETADISC-RBF: Discrimination of beta-barrel membrane proteins using RBF networks and PSSM profiles. Comput Biol Chem. 2008; 32(3):227-31

543.                        Zou L, Wang Z, Wang Y. Prediction of Outer Membrane Proteins Using Support Vector Machine with Combined Features. 2008; Chinese Journal of Biotechnology 24 (4): 651-658

544.                        Thein M, Bunikis I, Denker K, Larsson C, Cutler S, Drancourt M, Schwan TG, Mentele R, Lottspeich F, Bergström S, Benz R. Oms38 is the first identified pore-forming protein in the outer membrane of relapsing fever spirochetes. J Bacteriol. 2008;190(21):7035-42

545.                        Song, H., Sandie, R., Wang, Y., Andrade-Navarro, M.A., Niederweis, M. Identification of outer membrane proteins of Mycobacterium tuberculosis 2008 Tuberculosis 88 (6), pp. 526-544

546.                        Pedro Celso Nogueira Teixeira, Cristina Alves Magalhães de Souza, Mônica Santos de Freitas, Débora Foguel, Ernesto Raul Caffarena and Luiz Anastacio Alves. Predictions Suggesting a Participation of β-Sheet Configuration in the M2 Domain of the P2X7 Receptor: A Novel Conformation? Biophysical Journal Volume 96, Issue 3, 4 February 2009, Pages 951-963

547.                        Teixeira PC, de Souza CA, de Freitas MS, Foguel D, Caffarena ER, Alves LA. Predictions suggesting a participation of beta-sheet configuration in the M2 domain of the P2X(7) receptor: a novel conformation? Biophys J. 2009 Feb;96(3):951-63.

548.                        M. Michael Gromiha, Y. Yabuki, K. Imai, P. Horton, and K. Fukui Database Development and Discrimination Algorithms for Membrane Protein Functions  PWASET VOLUME 37 JANUARY 2009 ISSN 2070-3740

549.                        Singh P, Bandyopadhyay P, Bhattacharya S, Krishnamachari A, Sengupta S. Riboswitch detection using profile hidden Markov models. BMC Bioinformatics. 2009 Oct 8;10:325.

550.                        Shu-An Chen, Yu-Yen Ou and M. Michael Gromiha Topology Prediction of α-Helical and β-Barrel Transmembrane Proteins Using RBF Networks Lecture Notes in Computer Science, 2010, Volume 6215/2010, 642-649

551.                        Ayalew S, Confer AW, Hartson SD, Shrestha B. Immunoproteomic analyses of outer membrane proteins of Mannheimia haemolytica and identification of potential vaccine candidates. Proteomics. 2010 Jun;10(11):2151-64.

552.                        Ignas Bunikis Borrelia channel-forming proteins:  structure and function PhD Thesis, Umea University, 2010

553.                         Zou L, Wang Z, Wang Y, Hu F. Combined prediction of transmembrane topology and signal peptide of beta-barrel proteins: using a hidden Markov model and genetic algorithms. Comput Biol Med. 2010 Jul;40(7):621-8. Epub 2010 May 21

554.                        Ou YY, Chen SA, Gromiha MM. Classification of transporters using efficient radial basis function networks with position-specific scoring matrices and biochemical properties. Proteins. 2010 May 15;78(7):1789-97.

555.                        Gao QB, Ye XF, Jin ZC, He J.Improving discrimination of outer membrane proteins by fusing different forms of pseudo amino acid composition. Anal Biochem. 2010 Mar 1;398(1):52-9. Epub 2009 Oct 27.

556.                        Yang L, Li Y, Xiao R, Zeng Y, Xiao J, Tan F, Li M. Using auto covariance method for functional discrimination of membrane proteins based on evolution information. Amino Acids. 2010 May;38(5):1497-503. Epub 2009 Oct 7.

557.                        Lenhart TR, Akins DR. Borrelia burgdorferi locus BB0795 encodes a BamA orthologue required for growth and efficient localization of outer membrane proteins. Mol Microbiol. 2010 Feb;75(3):692-709. Epub 2009 Dec 16.

558.                        Abu Khweek A, Fetherston JD, Perry RD. Analysis of HmsH and its role in plague biofilm formation. Microbiology. 2010 May;156(Pt 5):1424-38. Epub 2010 Jan 21.

Papasaikas PK, Bagos PG, Litou ZI, Hamodrakas SJ. A novel method for GPCR recognition and family classification, using fingerprints derived from profile Hidden Markov Models. SAR QSAR Environ Res, 2003, 14(5-6): 413-420.  (Impact Factor: 2.238, citations: 19)

559.                        Lu F, Li J, Jiang Z. Computational identification and analysis of G protein-coupled receptor targets. Drug Development Research. 2007, 67(10): 771 – 780

560.                        Ashton M, Charlton MH, Schwarz MK, Thomas RJ, Whittaker M. The selection and design of GPCR ligands: From concept to the clinic. Combinatorial Chemistry and High Throuput Screening 2004, 7 (5): 441-452

561.                        Huang ES. Predicting ligands for orphan GPCRs. Drug Discov Today. 2005, 10(1): 69-73

562.                        Guo YZ, Li ML, Wang KL, Wen ZN, Lu MC, Liu LX, Jiang L. Fast fourier transform-based support vector machine for prediction of G-protein coupled receptor subfamilies. Acta Biochim Biophys Sin (Shanghai). 2005; 37(11): 759-66

563.                        Holden N, Freitas AA. Hierarchical classification of G-protein-coupled receptors with a PSO/ACO algorithm. Proceedings of the 2006 IEEE Swarm Intelligence Symposium, pp. 77-84.

564.                        Huang N, Chen H, Sun Z. CTKPred: an SVM-based method for the prediction and classification of the cytokine superfamily. Protein Eng Des Sel. 18(8): 365-8, 2005

565.                        Wang YF, Chen H, Zhou YH. Prediction and classification of human G-protein coupled receptors based on support vector machines. Genomics Proteomics Bioinformatics. 2005; 3 (4), 242-246

566.                        Trabanino R. Prediction of structure, function, and spectroscopic properties of G-protein-coupled receptors: methods and applications. PhD Thesis, California Institute of Technology, 2004

567.                        Fayyaz M, Khan A, Mujahid A, Kavokin A. Using multi level nearest neighbor classifiers for g-protein coupled receptor sub-families prediction. Lecture Notes in Computer Science 2007, 4463 LNBI, 564-576.

568.                        Eo H-S, Choi JP, Noh S-J, Hur C-G, Kim W. A combined approach for the classification of G protein-coupled receptors and its application to detect GPCR splice variants. Computational Biology and Chemistry 2007. 31 (4): 246-256

569.                        Fayyaz, Mudassir    Mujahid, Adnan    Khan, Asifullah    Choi, Tae-Sun    Iqbal, Nadeem. G-protein Coupled Receptor Subfamilies Prediction Based on Nearest Neighbor Approach. Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering,. BIBE 2007: 1348-1354

570.                        N. Holden and A.A. Freitas. Hierarchical classification of protein function with ensembles of rules and particle swarm optimisation. 2009, Soft Computing 13 (3), pp. 259-272

571.                        Holden, N., Freitas, A.A. Improving the performance of hierarchical classification with swarm intelligence. Lecture Notes in Computer Science, 4973 LNCS, pp. 48-60: 2008

572.                        Jingyi Yang   Deogun, J. G Protein-Coupled Receptor Classification at the Subfamily Level with Probabilistic Suffix Tree. IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology, 2006. CIBCB '06. 2006

573.                        Gupta, R., Mittal, A., Singh, K., Narang, V., Roy, S. Time-series approach to protein classification problem 2009 IEEE Engineering in Medicine and Biology Magazine 28 (4), pp. 32-37

574.                        Moriyama EN, Opiyo SO. Bioinformatics of Seven-Transmembrane Receptors in Plant Genomes. In Yalovsky S, Baluska F, Jones A (Eds) Integrated G Proteins Signaling in Plants. pp 251-277

575.                        Sonal Shrivastava, K. R. Pardasani, M. M. Malik. SVM Model for Identification of human GPCRs. JOURNAL OF COMPUTING, VOLUME 2, ISSUE 2, FEBRUARY 2010, ISSN 2151-9617

576.                        Peng ZL, Yang JY, Chen X. An improved classification of G-protein-coupled receptors using sequence-derived features. BMC Bioinformatics. 2010 Aug 9;11:420.

577.                        Li Z, Zhou X, Dai Z, Zou X. Classification of G-protein coupled receptors based on support vector machine with maximum relevance minimum redundancy and genetic algorithm. BMC Bioinformatics. 2010 Jun 16;11:325.       

Tsirpanlis G, Bagos P, Ioannou D, Bleta A, Marinou I, Lagouranis A, Chatzipanagiotou S, Nicolaou C. Serum albumin: a late reacting negative acute phase protein in clinically evident inflammation in dialysis patients. Nephrol Dial Transplant. 2005, 20:658-659 (Impact Factor:  3.568, citations: 1)

578.                        Baradaran A, Nasri H. Association of Serum C-Reactive Protein (CRP) with Some Nutritional Parameters of Maintenance Hemodialysis Patients. Pakistan Journal of Nutrition 4 (3): 175-182, 2005

Tsirpanlis G, Bagos P, Ioannou D, Bleta A, Marinou I, Lagouranis A, Chatzipanagiotou S, Nicolaou C. The variability and accurate assessment of microinflammation in haemodialysis patients. Nephrol Dial Transplant. 2004, 19(1): 150-157. (Impact Factor:  3.568, citations: 40)

579.                        Libetta C, Sepe V, Zucchi M, Portalupi V, Meloni F, Rampino T, Canton AD. The effect of sirolimus- or cyclosporine-based immunosuppression effects on T-cell subsets in vivo. Kidney Int. 2007;72 (1):114-120  

580.                        Cozzolino M, Galassi A, Biondi ML, Turri O, Papagni S, Mongelli N, Civita L, Gallieni M, Brancaccio D. Serum Fetuin-A Levels Link Inflammation and Cardiovascular Calcification in Hemodialysis Patients. Am J Nephrol. 2006; 26(5):423-429

581.                        Kalantar-Zadeh K, Balakrishnan VS. The kidney disease wasting: Inflammation, oxidative stress, and diet-gene interaction. Hemodial Int. 2006; 10(4): 315-25

582.                        Fanti P, Asmis R, Stephenson TJ, Sawaya BP, Franke AA. Positive effect of dietary soy in ESRD patients with systemic inflammation-correlation between blood levels of the soy isoflavones and the acute-phase reactants. Nephrol Dial Transplant. 2006; 21(8): 2239-46.

583.                        Stenvinkel P. New insights on inflammation in chronic kidney disease-genetic and non-genetic factors. 2006; Nephrologie et Therapeutique 2 (3), 111-119

584.                        Racki S, Zaputovic L, Mavric Z, Vujicic B, Dvornik S. C-reactive Protein Is a Strong Predictor of Mortality in Hemodialysis Patients. Ren Fail. 2006; 28(5): 427-33.

585.                        Caravaca F, Martin MV, Barroso S, Ruiz B, Hernandez-Gallego R. Do inflammatory markers add predictive information of death beyond that provided by age and comorbidity in chronic renal failure patients? Nephrol Dial Transplant. 2006; 21(6): 1575-81.

586.                        Biolo G, Amoroso A, Savoldi S, Bosutti A, Martone M, Pirulli D, Bianco F, Ulivi S, Bertok S, Artero M, Barazzoni R, Zanetti M, Grassi G, Guarnieri G, Panzetta G. Association of interferon-gamma +874A polymorphism with reduced long-term inflammatory response in haemodialysis patients. Nephrol Dial Transplant. 2006; 21(5):1317-22.

587.                        Pawlak K, Pawlak D, Mysliwiec M. Possible association between circulating vascular endothelial growth factor and oxidative stress markers in hemodialysis patients. Med Sci Monit. 2006; 12(4):CR181-186

588.                        Stenvinkel P. Inflammation in End-Stage Renal Disease - A Fire that Burns within. Contrib Nephrol. 2005; 149: 185-199.

589.                        Stenvinkel P, Pecoits R, Lindholm B. Gene polymorphism association studies in dialysis: The nutrition-inflammation axis. Semin Dialysis 18 (4): 322-330, 2005

590.                        Teruel JL, Marcen R, Ocana J, Fernandez-Lucas M, Rivera M, Tabernero G, Ortuno J. Clinical significance of C-reactive protein in patients on hemodialysis: A longitudinal study. Nephron Clinical Practice. 100 (4): C140-C145 2005

591.                        Nordfors L, Lindholm B, Stenvinkel P. End-stage renal disease - not an equal opportunity disease: the role of genetic polymorphisms. Journal of Internal Medicine. 258 (1): 1-12, 2005

592.                        Johnson DW. Time-integrated CRP level strongly predicts PD patient outcomes - Nice to know, but what should we do about it? Peritoneal Dialysis International. 25 (3): 234-237 2005

593.                        Kato A, Takita T, Maruyama Y, Hishida A. Chlamydial infection and progression of carotid atherosclerosis in patients on regular haemodialysis. Nephrology Dialysis Transplantation 2004, 19(10): 2539-2546

594.                        Terrier N, Senécal L, Dupuy A-M, Jaussent I, Delcourt C, Leray H Rafaelsen S, Bosc J-Y, Maurice F, Canaud B, Cristol J-P. Association between novel indices of malnutrition-inflammation complex syndrome and cardiovascular disease in hemodialysis patients. Hemodialysis International. 9(2): 159

595.                        Smith C, Myburgh KH. Treatment with Sutherlandia frutescens ssp. microphylla alters the corticosterone response to chronic intermittent immobilization stress in rats. South African Journal of Science. 2004; 100(3-4): 229-232

596.                        Wu Bibo, Zhang Liming, Hong Ying. Effects of Levocarnitine on Microinflammatory Status in Maintenance Hemodialysis Patients. Chinese Journal of Integrated Traditional and Western Nephrology, 2006 7 (7):398-401

597.                        Zhang LM. Wu BB. Tang Q. Hong Y. Yu Y. Effects of levocarnitine on microinflammation and oxidative stress status in maintenance hemodialysis patients. 2006; Pharmaceutical Care and Research 6 (3), 172-175

598.                        Wang Qi, Tu Wei-ping. Micro inflammation and chronic renal failure. Acta Academiae Medicinae Jiangxi. 2006; 46 (6):186-188

599.                        Feng Li-ping, Zhang Ling, Zhong Ling. The effect of vitamin E supplementation on oxidative stress and microinflammation state in patient with MHD. Chinese Journal of Practical internal Medicine. 2007; 27 (3): 215-217

600.                        Li Min Xia, Bi-Cheng Liu. Angiotensin II and micro-inflammatory response. INTERNATIONAL JOURNAL OF UROLOGY AND NEPHROLOGY. 2006; 26 (1):139-143

601.                        Axelsson . Fat tssue, Adipokines and Clinical Complications of Chronic Kidney Disease. Phd Thesis, Karolinska Institutet. 2006

602.                        Seung Duk Hwang, A Mechanism of Hemodialysis Vascular Access Stenosis. The Korean Journal of Nephrology, 2006, 25(5): 689-693

603.                        Dantzer R, Capuron L, Irwin MR, Miller AH, Ollat H, Hugh Perry V, Rousey S, Yirmiya R. Identification and treatment of symptoms associated with inflammation in medically ill patients. 2008, Psychoneuroendocrinology 33 (1), pp. 18-29

604.                        Bossola M, La Torre G, Giungi S, Tazza L, Vulpio C, Luciani G. Serum Albumin, Body Weight and Inflammatory Parameters in Chronic Hemodialysis Patients: A Three-Year Longitudinal Study. Am J Nephrol. 2008;28(3):405-412

605.                        Kalantar-Zadeh K, Anker SD, Horwich TB, Fonarow GC. Nutritional and anti-inflammatory interventions in chronic heart failure. Am J Cardiol. 2008;101(11A):89E-103E.

606.                        Panichi V, Rizza GM, Paoletti S, Bigazzi R, Aloisi M, Barsotti G, Rindi P, Donati G, Antonelli A, Panicucci E, Tripepi G, Tetta C, Palla R. Chronic inflammation and mortality in haemodialysis: effect of different renal replacement therapies. Results from the RISCAVID study. Nephrol Dial Transplant. 2008;23(7):2337-43

607.                        LaClair R, O'Neal K, Ofner S, Sosa MJ, Labarrere CA, Moe SM. Precision of biomarkers to define chronic inflammation in CKD. Am J Nephrol. 2008;28(5):808-12.

608.                         Chiu YL, Chen HY, Chuang YF, Hsu SP, Lai CF, Pai MF, Yang SY, Peng YS. Association of uraemic pruritus with inflammation and hepatitis infection in haemodialysis patients. Nephrol Dial Transplant. 2008;23(11):3685-9.

609.                         Wetmore JB, Lovett DH, Hung AM, Cook-Wiens G, Mahnken JD, Sen S, Johansen KL. Associations of interleukin-6, C-reactive protein and serum amyloid A with mortality in haemodialysis patients. Nephrology (Carlton). 2008 Sep 25

610.                        Lindblad, Y.T., Axelsson, J., Bárány, P., Celsi, G., Lindholm, B., Qureshi, A.R., Carrea, A., Canepa, A. Hyperinsulinemia and insulin resistance, early cardiovascular risk factors in children with chronic kidney disease 2008 Blood Purification 26 (6), pp. 518-525

611.                        Chiu, Y.-L., Chuang, Y.-F., Fang, K.-C., Liu, S.-K., Chen, H.-Y., Yang, J.-Y., Pai, M.-F., (...), Tsai, T.-J. Higher systemic inflammation is associated with poorer sleep quality in stable haemodialysis patients 2009 Nephrology Dialysis Transplantation 24 (1), pp. 247-251

612.                        Honda H, Ueda M, Kojima S, Mashiba S, Hirai Y, Hosaka N, Suzuki H, Mukai M, Watanabe M, Takahashi K, Shishido K, Akizawa T Assessment of Myeloperoxidase and Oxidative alpha(1)-Antitrypsin in Patients on Hemodialysis  CLINICAL JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY 4 (1): 142-151 JAN 2009

613.                        Elshamaa, M.F., Sabry, S., Galal, A., Koura, H., Kantoush, N., Rasheed, M., Thabet, E.H. Serum interleukin-10 levels and microinflammation in vascular access failure in egyptian children on hemodialysis, 2009         Journal of Clinical and Basic Cardiology 12 (1-4), pp. 18-23

614.                        Zhou, W.-X., Zheng, W.-B., Huang, X.-M., Zhang, Y., Nie, X.-Z., Li, H.-B., He, D., Xie, L.-Q. Effects of oxymatrine on microinflammatory state in patients undergoing continuous hemodialysis: A randomized controlled trial, 2009, Journal of Chinese Integrative Medicine 7 (8), pp. 736-740

615.                        Li PK, Cheng YL, Leung CB, Szeto CC, Chow KM, Kwan BC, Ng ES, Fok QW, Poon YL, Yu AW. Effect of membrane permeability on inflammation and arterial stiffness: a randomized trial. Clin J Am Soc Nephrol. 2010 Apr;5(4):652-8. Epub 2010 Mar 4.

616.                        Mistrík E, Bláha V, Dusilová-Sulková S, Andrýs C, Kalousová M, Sobotka L. Anti-inflammatory properties of high-density lipoprotein cholesterol in chronic hemodialysis patients: impact of intervention. J Ren Nutr. 2010 Nov;20(6):368-76. Epub 2010 Sep 15.

617.                        Balaforlu B, Eskiyoruk I, Kus B, Tozar M, Bekiroglu N, Koc M. Seasonal variation of C-reactive protein and atherosclerotic cardiovascular events in hemodialysis patients. Ren Fail. 2010;32(7):825-31.

618.                        Bonaterra, G. A.; Zugel, S.; Kinscherf, R. Novel Systemic Cardiovascular Disease Biomarkers Current Molecular Medicine, Volume 10, Number 2, March 2010 , pp. 180-205(26)

Tsirpanlis G, Bagos P, Ioannou D, Bleta A, Marinou I, Lagouranis A, Chatzipanagiotou S, Nicolaou C. Exploring Inflammation in Hemodialysis patients: Persistent and Superimposed Inflammation - a longitudinal study. Kidney Blood Press Res, 2004, 27:63-70. (Impact Factor:  1.268, citations: 18)

619.                        Joki N, Hase H, Tanaka Y, Takahashi Y, Saijyo T, Ishikawa H, Inishi Y, Imamura Y, Hara H, Tsunoda T, Nakamura M. Relationship between serum albumin level before initiating haemodialysis and angiographic severity of coronary atherosclerosis in end-stage renal disease patients. Nephrol Dial Transplant. 2006; 21(6): 1633-9.

620.                        do Nascimento MM, Stenvinkel P, Riella M, Lindholm B. Serum albumin: a late reacting negative acute phase protein in clinically evident inflammation in dialysis patients. (Author’s Reply) Nephrol Dial Transplant. 2005, 20: 659-660

621.                        Schwedler SB, Filep JG, Galle J, Wanner C, Potempa LA. C-reactive protein: A family of proteins to regulate cardiovascular function.  American Journal of Kidney Diseases. 2006 47 (2): 212-222

622.                        Prasad R. C-Reactive Protein for the Nephrologist. Nephrology Rounds, 2006, 7(6).

623.                        Nasri H. Serum C-Reactive Protein (CRP) in association with various nutritional parameters in maintenance hemodialysis patients. Bratisl Lek Lisky; 2005, 106(12): 390-395

624.                        Zang Xiao-Dong, SONG Bao-Li. The effect of huo xue fu shen capsule preparetion on the state of microinflammation in rat model of CRF. Journal Of Clinical Nephrology, 2006; 6(3):

625.                        Wu Y, Chen T, Feng SJ, Liu F. Effects of advanced glycosylation end products on the secretion function of monocyte in different dialysis-age patients. Journal of Clinical Rehabilitative Tissue Engineering Research  2007, 11 (21): 4140-4143

626.                        Barany P, Muller HJ. Maintaining control over haemoglobin levels: optimizing the management of anaemia in chronic kidney disease. Nephrol Dial Transplant. 2007; 22 Suppl 4:iv10-iv18.

627.                        LI Li, WANG Xiao-yun, LIU Dian-ge, LIU Bi-cheng, GAO Min. An association between microinflammation and arteriovenous fistula dysfunction in maintenance hemodialysis patients. Chinese Journal of Blood Purification. 2007; 6(10):538-542

628.                        Hung A, Pupim L, Yu C, Shintani A, Siew E, Ayus C, Hakim RM, Ikizler TA. Determinants of C-reactive protein in chronic hemodialysis patients: Relevance of dialysis catheter utilization. Hemodial Int. 2008; 12(2):236-243.

629.                        de Mutsert R, Grootendorst DC, Axelsson J, Boeschoten EW, Krediet RT, Dekker FW; NECOSAD Study Group. Excess mortality due to interaction between protein-energy wasting, inflammation and cardiovascular disease in chronic dialysis patients. Nephrol Dial Transplant. 2008; 23(9):2957-64.

630.                        Shah NR, Dumler F. Hypoalbuminaemia--a marker of cardiovascular disease in patients with chronic kidney disease stages II-IV. Int J Med Sci. 2008;5(6):366-70

631.                        de Mutsert, R., Grootendorst, D.C., Indemans, F., Boeschoten, E.W., Krediet, R.T., Dekker, F.W. Association Between Serum Albumin and Mortality in Dialysis Patients Is Partly Explained by Inflammation, and Not by Malnutrition 2009 Journal of Renal Nutrition 19 (2), pp. 127-135

632.                        Liu BC, Li L, Gao M, Wang YL, Yu JR Microinflammation is involved in the dysfunction of arteriovenous fistula in patients with maintenance hemodialysis CHINESE MEDICAL JOURNAL 121 (21): 2157-2161 5 2008

633.                        Amir Hayat, Dhiren Haria, Moro O Salifu. Erythropoietin stimulating agents in the management of anemia of chronic kidney disease. Patient Preference and Adherence 2008:2 195–200

634.                        Elshamaa, M.F., Sabry, S., Galal, A., Koura, H., Kantoush, N., Rasheed, M., Thabet, E.H. Serum interleukin-10 levels and microinflammation in vascular access failure in egyptian children on hemodialysis, 2009         Journal of Clinical and Basic Cardiology 12 (1-4), pp. 18-23

635.                        Simic-Ogrizovic, S., Dopsaj, V., Bogavac-Stanojevic, N., Obradovic, I., Stosovic, M., Radovic, M. Serum amyloid-A rather than C-reactive protein is a better predictor of mortality in hemodialysis patients, 2009 , Tohoku Journal of Experimental Medicine 219 (2), pp. 121-127

636.                        Balaforlu B, Eskiyoruk I, Kus B, Tozar M, Bekiroglu N, Koc M. Seasonal variation of C-reactive protein and atherosclerotic cardiovascular events in hemodialysis patients. Ren Fail. 2010;32(7):825-31.

Tsirpanlis G, Chatzipanagiotou S, Ioannidis A, Ifanti K, Bagos P, Lagouranis A, Poulopoulou C, Nicolaou C. The effect of viable Chlamydia pneumoniae on serum cytokines and adhesion molecules in hemodialysis patients. Kidney Int Suppl. 2003, 84: S72-5.  (Impact Factor:  6.418, citations: 6)

637.                        Jacek Rysz, Ewa Majewska, Robert A. Stolarek, Maciej Banach, Aleksandra Cialstrokkowska-Rysz, Zbigniew Baj.  Increased Levels of Soluble TNF-alpha Receptors and Cellular Adhesion Molecules in Patients Undergoing Bioincompatible Hemodialysis. American Journal of Nephrology 26 (5): 437-444

638.                        Sessa R. Chlamlydia pneumoniae as risk factor of cardiovascular disease in dialysis patients. Int J Artif Organs 2005; 28: 3 – 7

639.                        Wu LP, Chen LH, Zhang JS, Sun L, Zhang YQ. Protective effect of rhIL-1beta on pancreatic islets of alloxan-induced diabetic rats. World J Gastroenterol. 2004; 10(22): 3353-3355.

640.                        Al Aly Z, Edwards JC. Vascular biology in uremia: insights into novel mechanisms of vascular injury. Adv Chronic Kidney Dis. 2004; 11(3): 310-8.

641.                        Varagunam M, Finney H, Trevitt R, Sharples E, McCloskey DJ, Sinnott PJ, Raftery MJ, Yaqoob MM. Pretransplantation levels of C-reactive protein predict all-cause and cardiovascular mortality, but not graft outcome, in kidney transplant recipients. Am J Kidney Dis. 2004; 43(3): 502-7.

642.                        Zhou Tong, Sun Guizhi, Xiao Li, Kai-Yin Wu, Zhang Dongqing, Yu-Ying Chen, Hu Chen Nan. Relationship between adhesion molecules and dendritic cells in the tubulointerstitial lesions of IgA nephropathy. 2006; Chinese Journal of Nephrology Dialysis and Transplantation; 2004 13 (6): 530-533

Petsalakis ΕΙ, Bagos PG, Litou ΖΙ, Hamodrakas SJ.  N-terminal sequence-based prediction of subcellular location. BioSysBio: Bioinformatics and Systems Biology Conference. Edinburgh, UK.BMC Bioinformatics 2005, 6(Suppl 3):S11. (1 citation)

643.                        Vicentini R, Menossi M. TISs-ST: a web server to evaluate polymorphic translation initiation sites and their reflections on the secretory targets. BMC Bioinformatics 2007, 8:160

Bagos PG, Liakopoulos TD, Hamodrakas SJ. Faster Gradient Descent Training of Hidden Markov Models, Using Individual Learning Rate Adaptation. Proceedings of ICGI 2004 Lecture Notes In Artificial Intelligence, Vol. 3264, pp. 40-52. (Impact Factor: 0.515, citations: 3)

644.                        Yan Y, Guo B. Application of wavelet neural network (WNN) and gradient descent method (GDM) in natural image denoising. 2006; Journal of Computational Information Systems 2 (2): 625-631

645.                        Yunyi Yan, Baolong Guo, Wei Ni. Image Denoising: An Approach Based on Wavelet Neural Network and Improved Median Filtering. Proceedings of the 6th World Congress on Intelligent Control and Automation, June 21 - 23, 2006, Dalian, China

646.                        Andersson R, Bruder CE, Piotrowski A, Menzel U, Nord H, Sandgren J, Hvidsten TR, de Ståhl TD, Dumanski JP, Komorowski J. A Segmental Maximum A Posteriori Approach to Genome-wide Copy Number Profiling. Bioinformatics, 2008, in press