Bioinformatics

Contents

  1. 1 General readings
  2. 2 Tutorials published in journals
  3. 3 Lectures at the University of Central Greece
  4. 4 Video Lectures
    1. 4.1 Series 1
    2. 4.2 Series 2
    3. 4.3 Series 3
  5. 5 Important papers on Bioinformatics
    1. 5.1 Prediction methods for protein sequences
    2. 5.2 Prediction methods for membrane proteins
    3. 5.3 Machine learning methods
    4. 5.4 Sequence alignment
    5. 5.5 Comparative genomics
    6. 5.6 Proteomics
    7. 5.7 Prediction methods on DNA sequences
    8. 5.8 Text mining
    9. 5.9 Microarray analysis
    10. 5.10 Other

General readings

  • Webb Miller 10 Steps to Success in Bioinformatics, 2009 ISCB Accomplishment by a Senior Scientist Award
  • Eddy SR. "Antedisciplinary" science.PLoS Comput Biol. 2005 Jun;1(1):e6. [PDF]
  • Ouzounis CA, Valencia A. Early bioinformatics: the birth of a discipline--a personal view.Bioinformatics. 2003 Nov 22;19(17):2176-90. [PDF]
  • Ouzounis C. Bioinformatics and the theoretical foundations of molecular biology.Bioinformatics. 2002 Mar;18(3):377-8. [PDF]
  • Valencia A. Bioinformatics: biology by other means.Bioinformatics. 2002 Dec;18(12):1551-2.[PDF]
  • Roberts RJ. The early days of bioinformatics publishing.Bioinformatics. 2000 Jan;16(1):2-4.[PDF]
Tutorials in Bioinformatics

Tutorials published in journals

Lectures at the University of Central Greece

Video Lectures

Series 1

Series 2

Series 3

Important papers on Bioinformatics

Prediction methods for protein sequences

  • Burkhard Rost. Protein Structure Prediction in 1D, 2D,and 3D. [PDF] [HTML]
  • Rost B. Review: Protein Secondary Structure Prediction Continues to Rise. Journal of Structural Biology 134, 204–218 (2001) [PDF]
  • Kerstin M.L. Menne, Henning Hermjakob and Rolf Apweiler. A comparison of signal sequence prediction methods using a test set of signal peptides. Bioinformatics Vol. 16  no. 8, 741-742 (2000) [PDF]
  • Olof Emanuelsson, Søren Brunak, Gunnar von Heijne, Henrik Nielsen. Locating proteins in the cell using TargetP, SignalP, and related tools. Nature Protocols 2, 953-971 (2007). [PDF]
  • Nielsen H, Brunak S, von Heijne G. Machine learning approaches for the prediction of signal peptides and other protein sorting signals. Protein Eng. 1999;12(1):3-9. [PDF]
  • Gardy JL, Brinkman FS. Methods for predicting bacterial protein subcellular localization. Nat Rev Microbiol. 2006; 4(10):741-51. [PDF]
  • Eisenhaber B, Eisenhaber F.Prediction of posttranslational modification of proteins from their amino acid sequence.Methods Mol Biol. 2010;609:365-84. [PDF]
  • Bendtsen JD, Nielsen H, von Heijne G, Brunak S. Improved prediction of signal peptides: SignalP 3.0. Journal of molecular biology. 2004;340(4):783-95. [PDF]
  • Jones DT. Protein secondary structure prediction based on position-specific scoring matrices. Journal of molecular biology. 1999;292(2):195-202. [PDF]

Prediction methods for membrane proteins

  • M Punta, LR Forrest, H Bigelow, A Kernytsky, J Liu, B Rost. Membrane protein prediction methods. Methods, 2007, 41:460-474 [PDF]
  • Moller S, Croning MD, Apweiller R. Evaluation of methods for the prediction of membrane spanning regions. Bioinformatics, 2001, 17(7): 646-653 [PDF]
  • 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 [PDF]
  • Casadio R, Fariselli P, Martelli PL, Pierleoni A, Rossi I, von Heijne G -The state of the art of membrane protein structure prediction: from sequence to 3D structure- In: "Modern Genome Annotation: the Biosapiens Network" (Frishman D, Valencia A eds) Springer-Verlag( Austria), (2008, in press) ISBN: 978-3-211-75122-0 [PDF]
  • Krogh A, Larsson B, von Heijne G, Sonnhammer EL. Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. Journal of molecular biology. 2001;305(3):567-80. [PDF]
  • Tusnády GE, Simon I. The HMMTOP transmembrane topology prediction server. Bioinformatics (Oxford, England). 2001;17(9):849-50. [PDF]

Machine learning methods

  • Tarca AL, Carey VJ, Chen XW, Romero R, Drăghici S. Machine learning and its applications to biology. PLoS Comput Biol. 2007 Jun;3(6):e116. [PDF]
  • Needham CJ, Bradford JR, Bulpitt AJ, Westhead DR. A primer on learning in Bayesian networks for computational biology.PLoS Comput Biol. 2007 Aug;3(8):e129. [PDF]
  • Choo KH, Tong JC, Zhang L.Recent applications of Hidden Markov Models in computational biology.Genomics Proteomics Bioinformatics. 2004 May;2(2):84-96. [PDF]
  • Saeys Y, Inza I, Larranaga P.A review of feature selection techniques in bioinformatics.Bioinformatics. 2007 Oct 1;23(19):2507-17.[PDF]
  • Rognvaldsson T, You L.Why neural networks should not be used for HIV-1 protease cleavage site prediction. Bioinformatics. 2004 Jul 22;20(11):1702-9.[PDF]

Sequence alignment

  • Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997 Sep 1;25(17):3389-402 [PDF]
  • Robert C Edgar and Serafim Batzoglou. Multiple sequence alignment. Current Opinion in Structural Biology 2006, 16:368–373 [PDF]
  • Cédric Notredame. Recent progresses in multiple sequence alignment: a survey. Pharmacogenomics (2002)  3 (1), 131-144 [PDF]
  • Mullan L.Pairwise sequence alignment--it's all about us! Brief Bioinform. 2006 Mar;7(1):113-5.[PDF]
  • Mitrophanov AY, Borodovsky M. Statistical significance in biological sequence analysis.Brief Bioinform. 2006 Mar;7(1):2-24.[PDF]
  • Altschul SF, Bundschuh R, Olsen R, Hwa T. The estimation of statistical parameters for local alignment score distributions.Nucleic Acids Res. 2001 Jan 15;29(2):351-61.[PDF]
  • Spang R, Vingron M. Statistics of large-scale sequence searching. Bioinformatics (Oxford, England). 1998;14(3):279-84. [PDF]

Comparative genomics

  • Enright AJ, Iliopoulos I, Kyrpides NC, Ouzounis CA.Nature. Protein interaction maps for complete genomes based on gene fusion events.1999 Nov 4;402(6757):86-90.[PDF]
  • Alfonso Valencia and Florencio Pazos. Computational methods for the prediction of protein interactions. Current Opinion in Structural Biology 2002, 12:368–373 [PDF]
  • Tsoka S, Ouzounis CA. Recent developments and future directions in computational genomics.FEBS Lett. 2000 Aug 25;480(1):42-8.[PDF]

Proteomics

  • Benjamin F. Cravatt, Gabriel M. Simon& John R. Yates III. The biological impact of mass-spectrometry-based proteomics. Nature 450, 991-1000 (13 December 2007) | doi:10.1038/nature06525 [PDF]
  • Palagi PM, Hernandez P, Walther D, Appel RD. Proteome informatics I: bioinformatics tools for processing experimental data. Proteomics. 2006 Oct;6(20):5435-44.[PDF]
  • Lisacek F, Cohen-Boulakia S, Appel RD. Proteome informatics II: bioinformatics for comparative proteomics. Proteomics. 2006 Oct;6(20):5445-66. [PDF]

Prediction methods on DNA sequences

  • Catherine Mathé, Marie-France Sagot, Thomas Schiex and Pierre Rouzé. Current methods of gene prediction, their strengths and weaknesses. Nucleic Acids Research, 2002, Vol. 30, No. 19 4103-4117 [PDF]
  • Rogic S, Mackworth AK, Ouellette FB.Evaluation of gene-finding programs on mammalian sequences.Genome Res. 2001;11(5):817-32. [PDF]
  • Harrow J, Nagy A, Reymond A, Alioto T, Patthy L, Antonarakis SE, Guigó R. Identifying protein-coding genes in genomic sequences. Genome Biol. 2009;10(1):201. Epub 2009 Jan 30.[PDF]
  • Lee C, Wang Q.Bioinformatics analysis of alternative splicing.Brief Bioinform. 2005 Mar;6(1):23-33.[PDF]
  • Baxevanis AD. An overview of gene identification: approaches, strategies, and considerations.Curr Protoc Bioinformatics. 2004 Sep;Chapter 4:Unit4.1.[PDF]

Text mining

  • K. Bretonnel Cohen, Lawrence Hunter. Getting Started in Text Mining. PLoS Comput Biol 4(1): e20. doi:10.1371/journal.pcbi.0040020 [PDF]
  • Rzhetsky A, Seringhaus M, Gerstein MB (2009) Getting Started in Text Mining: Part Two. PLoS Comput Biol 5(7): e1000411. doi:10.1371/journal.pcbi.1000411 [PDF]
  • Aaron M. Cohen and William R. Hersh. A survey of current work in biomedical text mining. Briefings in Bioinformatics 2005 6(1):57-71; doi:10.1093/bib/6.1.57[PDF]
  • Marc Weeber, Jan A. Kors and Barend Mons. Online tools to support literature-based discovery in the life sciences. Briefings in Bioinformatics 2005 6(3):277-286; doi:10.1093/bib/6.3.277 [PDF]

Microarray analysis

  • M. Madan Babu. An Introduction to Microarray Data Analysis. [PDF] [supplementary material]
  • Hong F, Breitling R (2008) A comparison of meta-analysis methods for detecting differentially expressed genes in microarray experiments. Bioinformatics 24(3): 374-382 [PDF]
  • Hanai T, Hamada H, Okamoto M. Application of bioinformatics for DNA microarray data to bioscience, bioengineering and medical fields.J Biosci Bioeng. 2006 May;101(5):377-84.[PDF]

Other

  • Steel, M. and Penny, D., Parsimony, likelihood and the role of models in molecular phylogenetics. Molecular Biology and Evolution 17(6) 839-850.[PDF]
  • Jeong H, Tombor B, Albert R, Oltvai ZN, Barabasi AL. The large-scale organization of metabolic networks. Nature 2000 Oct 5;407(6804):651-4 [PDF]
  • Karlin S. Statistical signals in bioinformatics. PNAS September 20, 2005 vol. 102 no. 38 13355-13362 [PDF]
  • Susana Vinga and Jonas Almeida. Alignment-free sequence comparison—a review. 2003,  Bioinformatics Vol. 19 no. 4 2003, Pages 513-523 [PDF]
  • Schulze-Kremer S. Ontologies for molecular biology and bioinformatics.In Silico Biol. 2002;2(3):179-93. [HTML]
  • Stevens R, Goble CA, Bechhofer S.Ontology-based knowledge representation for bioinformatics. Brief Bioinform. 2000 Nov;1(4):398-414. [PDF]
  • Baxevanis AD.The importance of biological databases in biological discovery.Curr Protoc Bioinformatics. 2006 Mar;Chapter 1:Unit 1.1.[PDF]
  • Mooney S.Bioinformatics approaches and resources for single nucleotide polymorphism functional analysis.Brief Bioinform. 2005 Mar;6(1):44-56.[PDF]