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Gene/Protein Sequence Analysis

A Compilation of Bioinformatic Tools

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Molecular Biomethods Handbook

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References

  1. Venter JC, et al (2001) The sequence of the human genome. Science 291:1304–1351

    Article  PubMed  CAS  Google Scholar 

  2. Lander ES, et al (2001) Initial sequencing and analysis of the human genome. Nature 409:860–921

    Article  PubMed  CAS  Google Scholar 

  3. Rehm BH(2001) Bioinformatic tools for DNA/protein sequence analysis, functional assignment of genes and protein classification. Appl Microbiol Biotechnol 57:579–592

    Article  PubMed  CAS  Google Scholar 

  4. Ewing B, Hillier L, Wendl MC, Green P (1998) Base-calling of automated sequencer traces using phred. I. Accuracy assessment. Genome Res 8:175–185

    PubMed  CAS  Google Scholar 

  5. Ewing B, Green P (1998) Base-calling of automated sequencer traces using phred. II. Error probabilities. Genome Res 8:186–194

    PubMed  CAS  Google Scholar 

  6. Huang X, Madan A (1999) CAP3: A DNA sequence assembly program. Genome Res 9:868–877

    Article  PubMed  CAS  Google Scholar 

  7. Gordon D, Abajian C, Green P (1998) Consed: a graphical tool for sequence finishing. Genome Res 8:195–202

    PubMed  CAS  Google Scholar 

  8. Staden R (1996) The Staden Sequence Analysis Package. Mol Biotech 5:233–241

    Article  CAS  Google Scholar 

  9. Staden R (1984) Computer methods to locate signals in nucleic acid sequences. Nucleic Acids Res 12:505–519

    Article  PubMed  CAS  Google Scholar 

  10. Claverie JM (1997) Computational methods for the identification of genes in vertebrate genomic sequences. Hum Mol Genet 6:1735–1744

    Article  PubMed  CAS  Google Scholar 

  11. Guigo R (1997) Computational gene identification: an open problem. Comput Chem 21:215–222

    Article  PubMed  CAS  Google Scholar 

  12. Krogh A (1998) In: Salzberg SL, Searls D, Kasif S (eds) Computational methods in molecular biology. Elsevier, Amsterdam

    Google Scholar 

  13. Krogh A (1998) In: Bishop MJ (ed) Guide to human genome computing, 2nd edn. Academic, New York, pp. 261–274

    Chapter  Google Scholar 

  14. Delcher AL, Harmon D, Kasif S, White O, Salzberg SL (1999) Improved micro-bial gene identification with GLIMMER. Nucleic Acids Res 27:4636–4641

    Article  PubMed  CAS  Google Scholar 

  15. Guigo R, Agarwal P, Abril JF, Burset M, Fickett JW (2000) An assessment of gene prediction accuracy in large DNA sequences. Genome Res 10:1631–1642

    Article  PubMed  CAS  Google Scholar 

  16. Krogh A (2000) Using database matches with for HMMGene for automated gene detection in Drosophila. Genome Res 10:523–528

    Article  PubMed  CAS  Google Scholar 

  17. Shibuya T, Rigoutsos I (2002) Dictionary-driven prokaryotic gene finding. Nucleic Acids Res 30:2710–2725

    Article  PubMed  CAS  Google Scholar 

  18. Pedersen JS, Hein J (2003) Gene finding with a hidden Markov model of genome structure and evolution. Bioinformatics 19:219–227

    Article  PubMed  CAS  Google Scholar 

  19. Guo FB, Ou HY, Zhang CT (2003) ZCURVE: a new system for recognizing protein-coding genes in bacterial and archaeal genomes. Nucleic Acids Res 31: 1780–1789

    Article  PubMed  CAS  Google Scholar 

  20. Larsen TS, Krogh A (2003) EasyGene – a prokaryotic gene finder that ranks ORFs by statistical significance. BMC Bioinformat 4:21

    Article  Google Scholar 

  21. Gelfand MS (1995) Prediction of function in DNA sequence analysis. J Comput Biol 2:87–115

    Article  PubMed  CAS  Google Scholar 

  22. Sherriff A, Ott J (2001) Applications of neural networks for gene finding. Adv Genet 42:287–297

    Article  PubMed  CAS  Google Scholar 

  23. Fickett JW (1996) Finding genes by computer: the state of the art. Trends Genet 12:316–320

    Article  PubMed  CAS  Google Scholar 

  24. Zhang CT, Wang J, Zhang R (2002) Using a Euclid distance discriminant method to find protein coding genes in the yeast genome. Comput Chem 26:195–206

    Article  PubMed  CAS  Google Scholar 

  25. Bajic VB, Seah SH (2003) Dragon gene start finder: an advanced system for finding approximate locations of the start of gene transcriptional units. Genome Res 13:1923–1929

    PubMed  CAS  Google Scholar 

  26. Zhang MQ (1998) Statistical features of human exons and their flanking regions. Hum Mol Genet 7:919–932

    Article  PubMed  CAS  Google Scholar 

  27. Searls DB (1992) The linguistics of DNA. Am Sci 80:579–591

    Google Scholar 

  28. Durbin R, Eddy S, Krogh A, Mitchison G (1998) Biological sequence analysis: probabilistic models of proteins and nucleic acids. Cambridge University Press, Cambridge

    Book  Google Scholar 

  29. Krogh A, Mian IS, Haussler D (1994) A hidden Markov model that finds genes in E. coli DNA. Nucleic Acids Res 22:4768–4778

    Article  PubMed  CAS  Google Scholar 

  30. Cole ST, Brosch R, Parkhill J, et al (1998) Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence. Nature 393: 537–544

    Article  PubMed  CAS  Google Scholar 

  31. Thomas A, Skolnick M (1994) A probabilistic model for detecting coding regions in DNA sequences. IMA J Math Appl Med Biol 11:149–160

    Article  PubMed  CAS  Google Scholar 

  32. Henderson J, Salzberg S, Fasman K (1997) Finding genes in DNA with a hidden Markov model. J Comput Biol 4:127–141

    Article  PubMed  CAS  Google Scholar 

  33. Lukashin AV, Borodovsky M (1998) GeneMark hmm: new solutions for gene finding. Nucleic Acids Res 26:1107–1115

    Article  PubMed  CAS  Google Scholar 

  34. Salzberg SL, Pertea M, Delcher AL, Gardner MJ, Tettelin H (1999) Interpolated Markov models for eukaryotic gene finding. Genomics 59:24–31

    Article  PubMed  CAS  Google Scholar 

  35. Badger JH, Olsen GJ (1999) CRITICA: coding region identification tool invoking comparative analysis. Mol Biol Eyol 16:512–524

    CAS  Google Scholar 

  36. Bocs S, Cruveiller S, Vallenet D, Nuel G, Medigue C (2003) AMIGene: annotation of microbial genes. Nucleic Acids Res 31:3723–6

    Article  PubMed  CAS  Google Scholar 

  37. Besemer J, Lomsadze A, Borodovsky M (2001) GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions. Nucleic Acids Res 29:2607–2618

    Article  PubMed  CAS  Google Scholar 

  38. Yeramian E, Jones L (2003) GeneFizz: a web tool to compare genetic (coding/ non-coding) and physical (helix/coil) segmentations of DNA sequences. Gene discovery and evolutionary perspectives. Nucleic Acids Res 31:3843–3849

    Article  PubMed  CAS  Google Scholar 

  39. Kotlar D, Lavner Y (2003) Gene prediction by spectral rotation measure: a new method for identifying protein-coding regions. Genome Res 13:1930–1937

    PubMed  CAS  Google Scholar 

  40. Snyder E, Stormo G (1995) Identification of protein coding regions in genomic DNA. J Mol Biol 248:1–18

    Article  PubMed  CAS  Google Scholar 

  41. Reese MG, Eeckman FH, Kulp D, Haussler D (1997) Improved splice site detection in Genie. J Comput Biol 4:311–323

    Article  PubMed  CAS  Google Scholar 

  42. Burge C, Karlin S (1997) Prediction of complete gene structures in human genomic DNA. J Mol Biol 268:78–94

    Article  PubMed  CAS  Google Scholar 

  43. Xu Y, Uberbacher EC (1997) Automated gene identification in large-scale genomic sequences. J Comput Biol 4:325–338

    Article  PubMed  CAS  Google Scholar 

  44. Gelfand MS, Mironov AA, Pevzner PA (1996) Gene recognition via spliced sequence alignment. Proc Natl Acad Sci USA 93:9061–9066

    Article  PubMed  CAS  Google Scholar 

  45. Foissac S, Bardou P, Moisan A, Cros MJ, Schiex T (2003) EUGENE'HOM: a generic similarity-based gene finder using multiple homologous sequences. Nucleic Acids Res 31:3742–3745

    Article  PubMed  CAS  Google Scholar 

  46. Smith TE, Waterman MS (1981) Identification of common molecular subsequences. J Mol Biol 147:195–197

    Article  PubMed  CAS  Google Scholar 

  47. Yada T, Takagi T, Totoki Y, Sakaki Y, Takaeda Y (2003) DIGIT: a novel gene finding program by combining gene-finders. Pac Symp Biocomput 8:375–387

    Google Scholar 

  48. Quandt K, Frech K, Karas H, Wingender E, Werner T (1995) MatInd and MatInspector – new fast and versatile tools for detection of consensus matches in nucleotide sequence data. Nucleic Acids Res 23:4878–4884

    Article  PubMed  CAS  Google Scholar 

  49. Prestridge DS (1991) SIGNAL SCAN: a computer program that scans DNA sequences for eukaryotic transcriptional elements. CABIOS 7:203–206

    PubMed  CAS  Google Scholar 

  50. Wingender E, Chen X, Hehl R, et al (2000) TRANSFAC: an integrated system for gene expression regulation. Nucleic Acids Res 28:316–319

    Article  PubMed  CAS  Google Scholar 

  51. Prestridge DS (1995) Predicting Pol II Promoter Sequences Using Transcription Factor Binding Sites. J Mol Biol 249:923–932

    Article  PubMed  CAS  Google Scholar 

  52. Eddy SR (1996) Hidden Markov models. Curr Opin Struct Biol 6:361–365

    Article  PubMed  CAS  Google Scholar 

  53. Eddy SR (1998) Profile hidden Markov models. Bioinformatics 14:755–763

    Article  PubMed  CAS  Google Scholar 

  54. Baldi R, Brunak S (1998) Bioinformatics: the machine learning approach. MIT Press, Boston, MA

    Google Scholar 

  55. Korenberg MJ, David R, Hunter IW, Solomon JE (2000) Automatic classification of protein sequences into structure/function groups via parallel cascade identification: a feasibility study. Ann Biomed Eng 28:803–811

    Article  PubMed  CAS  Google Scholar 

  56. Thompson JD, Higgins, DG, Gibson TJ (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 22:4673–4680

    Article  PubMed  CAS  Google Scholar 

  57. Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG (1997) The CLUSTAL X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res 25:4876–4882

    Article  PubMed  CAS  Google Scholar 

  58. Nicholas KB, Nicholas HB, Jr, Deerfield DW, II (1997) GeneDoc: analysis and visualization of genetic variation. EMBNEW NEWS 4:14

    Google Scholar 

  59. Lake JA (1994) Reconstructing evolutionary trees from DNA and protein sequences: paralinear distances. Proc Natl Acad Sci USA 91: 1451–1459

    Google Scholar 

  60. Lockhart PJ, Steel MA, Hendy MD, Penny D (1994) Recovering evolutionary trees under a more realistic model of sequence. Mol Biol Evol 11:605–612

    PubMed  CAS  Google Scholar 

  61. Brocchieri L (2001) Phylogenetic inferences from molecular sequences: review and critique. Theor Popul Biol 59:27–40

    Article  PubMed  CAS  Google Scholar 

  62. Stewart CB (1993) The powers and pitfalls of parsimony. Nature 361:603–607

    Article  PubMed  CAS  Google Scholar 

  63. Attwood TK, Beck ME, Flower DR, Scordis P, Selley JN (1998) The PRINTS protein fingerprint database in its fifth year. Nucleic Acids Res 26:304–308

    Article  PubMed  CAS  Google Scholar 

  64. Page RD (1996) Tree View: an application to display phylogenetic trees on personal computers. Comput Appl Biosci 12:357–358

    PubMed  CAS  Google Scholar 

  65. Gasteiger E, Gattiker A, Hoogland C, Ivanyi I, Appel RD, Bairoch A (2003) ExPASy: the proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Res 31:3784–3788

    Article  PubMed  CAS  Google Scholar 

  66. Rost B (1996) PHD: predicting one-dimensional protein structure by profile based neural networks. Methods Enzymol 266:525–539

    Article  PubMed  CAS  Google Scholar 

  67. Eyrich VA, Rost B (2003) META-PP: single interface to crucial prediction servers. Nucleic Acids Res 31:3308–3310

    Article  PubMed  CAS  Google Scholar 

  68. Nielsen H, Engelbrecht J, Brunak S, von Heijne G (1997) Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites. Protein Eng 10:1–6

    Article  PubMed  CAS  Google Scholar 

  69. Hansen JE, Lund O, Tolstrup N, Gooley AA, Williams KL, Brunak S (1998) NetOglyc: Prediction of mucin type O-glycosylation sites based on sequence context and surface accessibility. Glycoconjugate J 15:115–130

    Article  CAS  Google Scholar 

  70. Hansen JE, Lund O, Rapacki K, Brunak S (1997) O-glycbase version 2.0 – a revised database of O-glycosylated proteins. Nucleic Acids Res 25:278–282

    Article  PubMed  CAS  Google Scholar 

  71. Hansen JE, Lund O, Rapacki K, et al (1995) Prediction of O-glycosylation of mammalian proteins: specificity patterns of UDP-GalNAc:-polypeptide N-acetyl-galactosaminyltransferase. Biochem J 308:801–813

    PubMed  CAS  Google Scholar 

  72. Blom N, Gammeltoft S, Brunak S (1999) Sequence- and structure-based prediction of eukaryotic protein phosphorylation sites. J Mol Biol 294:1351–1362

    Article  PubMed  CAS  Google Scholar 

  73. Blom N, Hansen J, Blaas D, Brunak S (1996) Cleavage site analysis in picorna-viral polyproteins: discovering cellular targets by neural networks. Protein Sci 5:2203–2216

    Article  PubMed  CAS  Google Scholar 

  74. Emanuelsson O, Nielsen H, von Heijne G (1999) ChloroP, a neural network-based method for predicting chloroplast transit peptides and their cleavage sites. Protein Sci 8:978–984

    Article  PubMed  CAS  Google Scholar 

  75. Cuff JA, Barton GJ (1999) Evaluation and improvement of multiple sequence methods for protein secondary structure prediction. Proteins 34:508–519

    Article  PubMed  CAS  Google Scholar 

  76. Sonnhammer ELL, von Heijne G, Krogh A (1998) A hidden Markov model for predicting transmembrane helices in protein sequences, In proceedings of the sixth intern conference on intelligent systems for molecular biology, (ISMB98), pp175–182

    Google Scholar 

  77. von Heijne G (1992) Membrane protein structure prediction, hydrophobicity analysis and the positive-inside rule. J Mol Biol 225:487–494

    Article  Google Scholar 

  78. Karplus K, Barrett C, Hughey R (1998) Hidden markov models for detecting remote protein homologies. Bioinformatics 14:846–856

    Article  PubMed  CAS  Google Scholar 

  79. Cserzo M, Wallin E, Simon I, von Heijne G, Elofsson A (1997) Prediction of transmembrane alpha-helices in procariotic membrane proteins: the dense alignment surface method. Protein Eng 10:673–676

    Article  PubMed  CAS  Google Scholar 

  80. Fischer D, Eisenberg DA (1996) Fold recognition using sequence-derived properties. Protein Sci 5:947–955

    Article  PubMed  CAS  Google Scholar 

  81. Elofsson A, Fischer D, Rice DW, LeGrand S, Eisenberg DA (1996) Study of combined structure-sequence profiles. Folding Design 1:451–461

    Article  PubMed  CAS  Google Scholar 

  82. Karplus K, Karchin R, Draper J, et al (2003) Combining local-structure, fold-recognition, and new-fold methods for protein structure prediction. Proteins 53(Suppl 6):491–496

    Article  PubMed  CAS  Google Scholar 

  83. Peitsch MC (1995) Protein modelling by E-mail. BioTechnology 13:658–660

    Article  CAS  Google Scholar 

  84. Peitsch MC (1996) ProMod and Swiss-Model: internet-based tools for automated comparative protein modelling. Biochem Soc Trans 24:274–279

    PubMed  CAS  Google Scholar 

  85. Guex N, Peitsch MC (1997) SWISS-MODEL and the Swiss-PdbViewer: an environment for comparative protein modelling. Electrophoresis 18:2714–2723

    Article  PubMed  CAS  Google Scholar 

  86. Lund O, Frimand K, Gorodkin J, et al (1997) Protein distance constraints predicted by neural networks and probability density functions. Protein Eng 10:1241–1248

    Article  PubMed  CAS  Google Scholar 

  87. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. J Mol Biol 215:403–410

    PubMed  CAS  Google Scholar 

  88. Altschul SF (1991) Amino acid substitution matrices from an information theoretic perspective. J Mol Biol 219:555–565

    Article  PubMed  CAS  Google Scholar 

  89. Altschul SF, Gish W (1996) Local alignment statistics. Methods Enzymol. 266:460–480

    Article  PubMed  CAS  Google Scholar 

  90. Rost B, Schneider R, Sander C (1997) Protein fold recognition by prediction-based threading. J Mol Biol 270:471–480

    Article  PubMed  CAS  Google Scholar 

  91. Dayhoff MO, Barker WC, Hunt LT (1983) Establishing homologies in protein sequences. Methods Enzymol 91:524–545

    Article  PubMed  CAS  Google Scholar 

  92. Henikoff S, Henikoff JG (1992) Amino acid substitution matrices from protein blocks. Proc Natl Acad Sci USA 89:10,915–10,919

    Article  CAS  Google Scholar 

  93. Pearson WR (1995) Comparison of methods for searching protein sequence databases. Protein Sci 4:1145–1160

    Article  PubMed  CAS  Google Scholar 

  94. Karlin S, Altschul SE (1990) Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes. Proc Natl Acad Sci USA 87:2264–2268

    Article  PubMed  CAS  Google Scholar 

  95. Wootton JC (1994) Non-globular domains in protein sequences: automated segmentation using complexity measures. Comput Chem 18:269–285

    Article  PubMed  CAS  Google Scholar 

  96. Altschul SF, Madden TL, Schäffer AA, et al (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25:3389–3402

    Article  PubMed  CAS  Google Scholar 

  97. Pearson WR, Lipman DJ (1988) Improved tools for biological sequence comparison. Proc Natl Acad Sci USA 85:2444–2448

    Article  PubMed  CAS  Google Scholar 

  98. Martin AC, Orengo CA, Hutchinson EG, et al (1998) Protein folds and functions. Structure 6:875–884

    Article  PubMed  CAS  Google Scholar 

  99. McGuffin LJ, Bryson K, Jones DT (2001) What are the baselines for protein fold recognition? Bioinformatics 17:63–72

    Article  PubMed  CAS  Google Scholar 

  100. Bairoch A (1991) PROSITE: a dictionary of sites and patterns in proteins. Nucleic Acids Res 19:2241–2245

    PubMed  CAS  Google Scholar 

  101. Bairoch A, Bucher P, Hofmann K (1997) The PROSITE database, its status in 1997. Nucleic Acids Res 25:217–221

    Article  PubMed  CAS  Google Scholar 

  102. Bucher P, Karplus K, Moeri, N, Hofmann K (1996) A flexible motif search technique based on generalized profiles. Comput Chem 20:3–23

    Article  PubMed  CAS  Google Scholar 

  103. Sonnhammer EL, Kahn D (1994) Modular arrangement of proteins as inferred from analysis of homology. Protein Sci 3:482–492

    Article  PubMed  CAS  Google Scholar 

  104. Corpet F, Gouzy J, Kahn D (1998) The ProDom database of protein domain families. Nucleic Acids Res 26:323–326

    Article  PubMed  CAS  Google Scholar 

  105. Sonnhammer EL, Eddy SR, Durbin R (1997) Pfam: a comprehensive database of protein domain families based on seed alignments. Proteins 28:405–420

    Article  PubMed  CAS  Google Scholar 

  106. Bateman A, Birney E, Cerruti L, et al (2002) The Pfam protein families database. Nucleic Acids Res 30:276–280

    Article  PubMed  CAS  Google Scholar 

  107. Apweiler R, Attwood TK, Bairoch A, et al (2001) The InterPro database, an integrated documentation resource for protein families, domains and functional sites. Nucleic Acids Res 29:37–40

    Article  PubMed  CAS  Google Scholar 

  108. Mulder NJ, Apweiler R, Attwood TK, et al (2003) The InterPro Database, 2003 brings increased coverage and new features. Nucleic Acids Res 31:315–8

    Article  PubMed  CAS  Google Scholar 

  109. Rawlings ND, O'Brien E, Barrett AJ (2002) MEROPS: the protease database. Nucleic Acids Res 30:343–346

    Article  PubMed  CAS  Google Scholar 

  110. Storm CE, Sonnhammer EL (2001) NIFAS: visual analysis of domain evolution in proteins. Bioinformatics 17:343–348

    Article  PubMed  CAS  Google Scholar 

  111. Schultz J, Milpetz F, Bork P, Ponting, CP (1998) SMART, a simple modular architecture research tool: identification of signaling domains. Proc Natl Acad Sci USA 95:5857–5864

    Article  PubMed  CAS  Google Scholar 

  112. Schultz J, Copley RR, Doerks T, Ponting CP, Bork P (2000) SMART: a web-based tool for the study of genetically mobile domains. Nucleic Acids Res 28:231–234

    Article  PubMed  CAS  Google Scholar 

  113. Letunic I, Goodstadt L, Dickens NJ, et al (2002) Recent improvements to the SMART domain-based sequence annotation resource. Nucleic Acids Res 30:242–244

    Article  PubMed  CAS  Google Scholar 

  114. Pietrokovski S, Henikoff JG, Henikoff S (1996) The Blocks database–a system for protein classification. Nucleic Acids Res 24:197–200

    Article  PubMed  CAS  Google Scholar 

  115. Attwood TK, Flower DR, Lewis AP, et al (1999) PRINTS prepares for the new millennium. Nucleic Acids Res 27:220–225

    Article  PubMed  CAS  Google Scholar 

  116. Silverstein KA, Shoop E, Johnson JE, Retzel EF (2001) MetaFam: a unified classification of protein families. I. Overview and statistics. Bioinformatics 17:249– 261

    Article  PubMed  CAS  Google Scholar 

  117. Yuan YP, Eulenstein O, Vingron M, Bork P (1998) Towards detection of ortho-logues in sequence databases. Bioinformatics 14:285–289

    Article  PubMed  CAS  Google Scholar 

  118. Bernstein FC, Koetzle TF, Williams GJ, et al (1977) The Protein Data Bank. A computer-based archival file for macromolecular structures. Eur J Biochem 80:319–324

    Article  PubMed  CAS  Google Scholar 

  119. Berman HM, Westbrook J, Feng Z, et al (2000) The Protein Data Bank. Nucleic Acids Res 28:235–242

    Article  PubMed  CAS  Google Scholar 

  120. Murzin AG, Brenner SE, Hubbard T, Chothia C (1995) SCOP: a structural classification of proteins database for the investigation of sequences and structures. J Mol Biol 247:536–540

    PubMed  CAS  Google Scholar 

  121. Orengo CA, Michie AD, Jones S, Jones DT, Swindells MB, Thomton JM (1997) CATH–a Hierarchic classification of protein domain structures. Structure 5: 1093–1108

    Article  PubMed  CAS  Google Scholar 

  122. Pearl FMG, Lee D, Bray JE, Sillitoe I, Todd AE, Harrison AP, Thomton JM, Orengo CA (2000) Assigning genomic sequences to CATH. Nucleic Acids Res 28:277–282

    Article  PubMed  CAS  Google Scholar 

  123. Peitsch MC, Jongeneel V (1993) A 3- dimensional model for the CD40 ligand predicts that it is a compact trimer similar to the tumor necrosis factors. Int Immunol 5:233–238

    Article  PubMed  CAS  Google Scholar 

  124. Schwede T, Kopp J, Guex N, Peitsch MC (2003) SWISS-MODEL: an automated protein homology-modeling server. Nucleic Acids Res 31:3381–3385

    Article  PubMed  CAS  Google Scholar 

  125. Guex N, Peitsch MC (1997) SWISS-MODEL and the Swiss-Pdb Viewer: an environment for comparative protein modeling. Electrophoresis 18:2714–2723

    Article  PubMed  CAS  Google Scholar 

  126. Combet C, Jambon M, Deleage G, Geourjon C (2002) Geno3D: automatic comparative molecular modelling of protein. Bioinformatics 18:213–214

    Article  PubMed  CAS  Google Scholar 

  127. Lambert C, Leonard N, De Bolle X, Depiereux E (2002) ESyPred3D: prediction of proteins 3D structures. Bioinformatics 18:1250–1256

    Article  PubMed  CAS  Google Scholar 

  128. Bader GD, Betel D, Hogue CW (2003) BIND: the Biomolecular Interaction Network Database. Nucleic Acids Res 31:248–250

    Article  PubMed  CAS  Google Scholar 

  129. Xenarios I, Rice DW, Salwinski L, Baron MK, Marcotte EM, Eisenberg D (2000) DIP: The Database of Interacting Proteins. Nucleic Acids Res 28:289–291

    Article  PubMed  CAS  Google Scholar 

  130. Levinthal C, Wodak SJ, Kahn P, Dadivanian AK (1975) Hemoglobin interaction in sickle cell fibers. I. Theoretical approaches to the molecular contacts. Proc Natl Acad Sci USA 72:1330–1334

    Article  PubMed  CAS  Google Scholar 

  131. Wodak SJ, Janin J (1978) Computer analysis of protein-protein interaction. J Mol Biol 124:323–342

    Article  PubMed  CAS  Google Scholar 

  132. Janin J, Henrick K, Moult J, et al (2003) CAPRI: a Critical Assessment of PRedicted Interactions. Proteins 52:2–9

    Article  PubMed  CAS  Google Scholar 

  133. Taylor RD, Jewsbury PJ, Essex JW (2002) A review of protein-small molecule docking methods. J Comput Aided Mol Des 16:151–166

    Article  PubMed  CAS  Google Scholar 

  134. Read TD, Peterson SN, Tourasse N, et al (2003) The genome sequence of Bacillus anthracis Ames and comparison to closely related bacteria. Nature 423:81–86

    Article  PubMed  CAS  Google Scholar 

  135. Ivanova N, Sorokin A, Anderson I, et al (2003) Genome sequence of Bacillus cereus and comparative analysis with Bacillus anthracis. Nature 423:87–91

    Article  PubMed  CAS  Google Scholar 

  136. Smith DR (1996) Microbial pathogen genomes – new strategies for identifying therapeutics and vaccine targets. Trends Biotechnol 14:290–293

    Article  PubMed  CAS  Google Scholar 

  137. Tatusov RL, Koonin EV, Lipman DJ (1997) A genomic perspective on protein families. Science 278:631–637

    Article  PubMed  CAS  Google Scholar 

  138. Tatusov, RL, Natale DA, Garkavtsev IV, et al (2001) The COG database: new developments in phylogenetic classification of proteins from complete genomes. Nucleic Acids Res 29:22–28

    Article  PubMed  CAS  Google Scholar 

  139. Wheeler DL, Church DM, Federhen S, et al (2003) Database resources of the National Center for Biotechnology. Nucleic Acids Res 31:28–33

    Article  PubMed  CAS  Google Scholar 

  140. Edgar R, Domrachev M, Lash AE (2002) Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res 30:207–210

    Article  PubMed  CAS  Google Scholar 

  141. Rehm BHA, Reinecke F (2004) Evaluation of proteomic techniques: applications and potential. Curr Proteomics 1:103–111

    Article  CAS  Google Scholar 

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Authors and Affiliations

  1. Institute of Molecular BioSciences, Massey University, Palmerston North, New Zealand

    Bernd H. A. Rehm

  2. Institut für Medizinische Physik und Biophysik, Elektronenmikroskopie und Analytik, Universitätsklinikum Münster Westfälische Wilhelms-Universität, Münster, Germany

    Frank Reinecke

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  1. School of Life Sciences, University of Hertfordshire, Hatfield, Hertfordshire, UK

    John M. Walker (Professor Emeritus) & Ralph Rapley (Professor Emeritus) & 

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Rehm, B.H.A., Reinecke, F. (2008). Gene/Protein Sequence Analysis. In: Walker, J.M., Rapley, R. (eds) Molecular Biomethods Handbook. Springer Protocols Handbooks. Humana Press. https://doi.org/10.1007/978-1-60327-375-6_22

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  • DOI: https://doi.org/10.1007/978-1-60327-375-6_22

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-60327-370-1

  • Online ISBN: 978-1-60327-375-6

  • eBook Packages: Springer Protocols

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