Bioinformatics

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

• • Tutorial in Bioinformatics, Sequence and Structural Alignment

  • Various Tutorials and other related educational resources at NCBI

• Bioinformatics: A Tutorial for Beginners

• Bioinformatics Tutorials Series (BITS)

• Protein sequence analysis: A practical guide

• A collection of tutorials in Bioinformatics

• Programs for Biological sequence analysis by Peter Sestoft

Tutorials published in journals

• • A series of tutorials published in Nature Biotechnology (EM, HMM, NN, SVM etc)

  • A series of tutorials published in Trends Guide to Bioinformatics (alignment, prediction, databases etc)

Lectures at the University of Thessaly

• Bioinformatics I

• Bioinformatics II

Video Lectures

Series 1

• Tutorial: Overview of the NCBI Bioinformatics Website

• Tutorial: The PubMed Literature Database at NCBI

• Tutorial: Interpretation (part I of II) of BLAST Results at NCBI

• Tutorial: Interpretation of Blast Results at NCBI, part II

• Tutorial: Looking up Protein and Gene Information at NCBI

• Tutorial: Examining the 3D Structure of Rhodopsin at NCBI

• Tutorial: The FASTA Data Record Format

• Tutorial: The OMIM Database at NCBI

• Tutorial: Overview of KEGG Bioinformatics Website

• Tutorial: Overview of the UniProt Bioinformatics Website

Series 2

• Bioinformatics Tutorials (Lesson 1):Using SwissProt database to search for a specific protein

  • Bioinformatics Tutorials (Lesson 2):Using BLAST to search for similarities

• Bioinformatics Tutorials (Lesson 3):Using TMHMM method to locate transmembrane helices

• Bioinformatics Tutorials (Lesson 4):Using ClustalW to do a multiple sequence alignment

• Bioinformatics Tutorials (Lesson 5):Using SABLE program to predict protein secondary structure

• Bioinformatics Tutorials (Lesson 6):Using ORF Finder program to locate Open Reading Frames

• Bioinformatics Tutorials (Lesson 7):Using GenMark for a more sophisticated ORF prediction

• Bioinformatics Tutorials (Lesson 8):Using Genomescan to parse genomes (find exons or coding regions)

• Bioinformatics Tutorials (Lesson 9) Part 1:Using PHYLIP to build phylogenetic trees

• Bioinformatics Tutorials (Lesson 9) Part 2:Using PHYLIP to build phylogenetic trees

Series 3

• Biological Sequence Analysis I

• Biological Sequence Analysis II

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]