Abstract
The rapid development of efficient, automated DNA-sequencing methods has strongly advanced the genome-sequencing era, culminating in the determination of the entire human genome in 2001 (1,2). An enormous amount of DNA sequence data are available and databases still grow exponentially (see Fig. 1). Analysis of this overwhelming amount of data, including hundreds of genomes from both prokaryotes and eukaryotes, has given rise to the field of bioinformatics. Development of bioinformatic tools has evolved rapidly in order to identify genes that encode functional proteins or RNA. This is an important task, considering that even in the best studied bacterium Escherichia coli more than 30‰ of the identified open reading frames (ORFs) represent hypothetical genes with no known function. Future challenges of genome-sequence analysis will include the understanding of diseases, gene regulation, and metabolic pathway reconstruction. In addition, a set of methods for protein analysis summarized under the term proteomics holds tremendous potential for biomedicine and biotechnology (141). The large number of bioinformatic tools that have been made available to scientists during the last few years has presented the problem of which to use and how best to obtain scientifically valid answers (3). In this chapter, we will provide a guide for the most efficient way to analyze a given sequence or to collect information regarding a gene, protein, structure, or interaction of interest by applying current publicly available software and databases that mainly use the World Wide Web. All links to services or download sites are given in the text or listed in Table 1; the succession of tools is briefly summarized in Fig. 2.
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References
Venter, J. C. et al (2001) The sequence of the human genome. Science 291, 1304–1351.
Lander, E. S. et al (2001) Initial sequencing and analysis of the human genome. Nature 409, 860–921.
Rehm B.H. (2001) Bioinformatic tools for DNA/protein sequence analysis, functional assignment of genes and protein classification. Appl. Microbiol. Biotechnol. 57, 579–592.
Ewing, B., Hillier, L., Wendl, M. C., and Green, P. (1998) Base-calling of automated sequencer traces using phred. I. Accuracy assessment. Genome Res. 8, 175–185.
Ewing, B. and Green, P. (1998) Base-calling of automated sequencer traces using phred. II. Error probabilities. Genome Res. 8, 186–194.
Huang, X. and Madan, A. (1999) CAP3: A DNA sequence assembly program. Genome Res. 9, 868–877.
Gordon, D., Abajian, C., and Green, P. (1998) Consed: a graphical tool for sequence finishing. Genome Res. 8, 195–202.
Staden, R. (1996) The Staden Sequence Analysis Package. Mol. Biotech. 5, 233–241.
Staden, R. (1984) Computer methods to locate signals in nucleic acid sequences. Nucleic Acids Res. 12, 505–519.
Claverie, J.-M. (1997) Computational methods for the identification of genes in vertebrate genomic sequences. Hum. Mol. Genet. 6, 1735–1744.
Guigo, R. (1997) Computational gene identification: an open problem. Comput. Chem. 21, 215–222.
Krogh, A. (1998) In Computational Methods in Molecular Biology (Salzberg, S. L., Searls, D., and Kasif, S., eds.), Elsevier, Amsterdam.
Krogh, A. (1998) In Guide to Human Genome Computing (Bishop, M. J., ed.), 2nd ed. Academic, New York, pp. 261–274.
Delcher, A. L., Harmon, D., Kasif, S., White, O., and Salzberg, S. L. (1999) Improved microbial gene identification with GLIMMER. Nucleic Acids Res. 27, 4636–4641.
Guigo, R., Agarwal, P., Abril, J. F., Burset, M., and Fickett, J. W. (2000) An assessment of gene prediction accuracy in large DNA sequences. Genome Res. 10, 1631–1642.
Krogh, A. (2000) Using database matches with for HMMGene for automated gene detection in Drosophila. Genome Res. 10, 523–5
Shibuya, T. and Rigoutsos, I. (2002) Dictionary-driven prokaryotic gene finding. Nucleic Acids Res. 30, 2710–2725.
Pedersen, J. S. and Hein, J. (2003) Gene finding with a hidden Markov model of genome structure and evolution. Bioinformatics 19, 219–227.
Guo, F. B., Ou, H. Y., and Zhang, C. T. (2003) ZCURVE: a new system for recognizing proteincoding genes in bacterial and archaeal genomes. Nucleic Acids Res. 31, 1780–1789.
Larsen, T. S., Krogh, A. (2003) EasyGene—a prokaryotic gene finder that ranks ORFs by statistical significance. BMC Bioinformat. 4, 21.
Gelfand, M. S. (1995) Prediction of function in DNA sequence analysis. J. Comput. Biol. 2, 87–115.
Sherriff, A. and Ott, J. (2001) Applications of neural networks for gene finding. Adv. Genet. 42, 287–297.
Fickett, J. W. (1996) Finding genes by computer: the state of the art. Trends Genet. 12, 316–320.
Zhang, C. T., Wang, J., and Zhang, R. (2002) Using a Euclid distance discriminant method to find protein coding genes in the yeast genome. Comput. Chem. 26, 195–206.
Bajic, V. B. and Seah, S. H. (2003) Dragon gene start finder: an advanced system for finding approximate locations of the start of gene transcriptional units. Genome Res. 13, 1923–1929.
Zhang, M. Q. (1998) Statistical features of human exons and their flanking regions. Hum. Mol. Genet. 7, 919–932.
Searls, D. B. (1992) The linguistics of DNA. Am. Sci. 80, 579–591.
Durbin, R., Eddy, S., Krogh, A., and Mitchison, G. (1998) Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic acids. Cambridge University Press, Cambridge.
Krogh, A., Mian, I. S., and Haussler, D. (1994) A hidden Markov model that finds genes in E. coli DNA. Nucleic Acids Res. 22, 4768–4778.
Cole, S. T., Brosch, R., Parkhill, J., et al. (1998) Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence. Nature 393, 537–544.
Thomas, A. and Skolnick, M. (1994) A probabilistic model for detecting coding regions in DNA sequences. IMA J. Math. Appl. Med. Biol. 11, 149–160.
Henderson, J., Salzberg, S., and Fasman, K. (1997) Finding genes in DNA with a hidden Markov model. J. Comput. Biol. 4, 127–141.
Lukashin, A. V. and Borodovsky, M. (1998) GeneMark hmm: new solutions for gene finding. Nucleic Acids Res. 26, 1107–1115.
Salzberg, S. L., Pertea, M., Delcher, A. L., Gardner, M. J., and Tettelin, H. (1999) Interpolated Markov models for eukaryotic gene finding. Genomics 59, 24–31.
Badger, J. H. and Olsen, G. J. (1999) CRITICA: coding region identification tool invoking comparative analysis. Mol. Biol. Evol. 16, 512–524.
Bocs, S., Cruveiller, S., Vallenet, D., Nuel, G., and Medigue, C. (2003) AMIGene: annotation of microbial genes. Nucleic Acids Res. 31, 3723–6.
Besemer, J., Lomsadze, A., and 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.
Yeramian, E. and 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.
Kotlar, D. and Lavner, Y. (2003) Gene prediction by spectral rotation measure: a new method for identifying protein-coding regions. Genome Res. 13, 1930–1937.
Snyder, E. and Stormo, G. (1995) Identification of protein coding regions in genomic DNA. J. Mol. Biol. 248, 1–18.
Reese, M. G., Eeckman, F. H., Kulp, D., and Haussler, D. (1997) Improved splice site detection in Genie. J. Comput. Biol. 4, 311–323.
Burge, C. and Karlin, S. (1997) Prediction of complete gene structures in human genomic DNA. J. Mol. Biol. 268, 78–94.
Xu, Y. and Überbacher, E. C. (1997) Automated gene identification in large-scale genomic sequences. J. Comput. Biol. 4, 325–338.
Gelfand, M. S., Mironov, A. A., and Pevzner, P. A. (1996) Gene recognition via spliced sequence alignment. Proc. Natl. Acad. Sci. USA 93, 9061–9066.
Foissac, S., Bardou, P., Moisan, A., Cros, M. J., and Schiex, T. (2003) EUGENE’HOM: a generic similarity-based gene finder using multiple homologous sequences. Nucleic Acids Res. 31, 3742–3745.
Smith, T. E. and Waterman, M. S. (1981) Identification of common molecular subsequences. J. Mol. Biol. 147, 195–197.
Yada, T., Takagi, T., Totoki, Y., Sakaki, Y., and Takaeda Y. (2003) DIGIT: a novel gene finding program by combining gene-finders. Pac. Symp. Biocomput. 2003, 375–387.
Quandt, K., Frech, K., Karas, H., Wingender, E., and 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.
Prestridge, D. S. (1991) SIGNAL SCAN: a computer program that scans DNA sequences for eukaryotic transcriptional elements. CABIOS 7, 203–206.
Wingender, E., Chen, X., Hehl, R., et al. (2000) TRANSFAC: an integrated system for gene expression regulation. Nucleic Acids Res. 28, 316–319.
Prestridge, D. S. (1995) Predicting Pol II Promoter Sequences Using Transcription Factor Binding Sites. J. Mol. Biol. 249, 923–932.
Eddy, S. R. (1996) Hidden Markov models. Curr. Opin. Struct. Biol. 6, 361–365.
Eddy, S. R. (1998) Profile hidden Markov models. Bioinformatics 14, 755–763.
Baldi, R. and Brunak, S. (1998) Bioinformatics: The Machine Learning Approach. MIT Press, Boston, MA.
Korenberg, M. J., David, R., Hunter, I. W., and Solomon, J. E. (2000) Automatic classification of protein sequences into structure/function groups via parallel cascade identification: a feasibility study. Ann. Biomed. Eng. 28, 803–811.
Thompson, J. D., Higgins, D. G., and Gibson, T. J. (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.
Thompson, J. D., Gibson, T. J., Plewniak, F., Jeanmougin, F., and Higgins, D. G. (1997) The CLUSTAL X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res. 25, 4876–4882.
Nicholas, K. B., Nicholas, H. B., Jr., and Deerfield, D. W., II. (1997) GeneDoc: analysis and visualization of genetic variation. EMBNEW.NEWS 4, 14.
Lake, J. A. (1994) Reconstructing evolutionary trees from DNA and protein sequences: paralinear distances. Proc. Natl. Acad. Sci. USA 91, 1451–1459.
Lockhart, P. J., Steel, M. A., Hendy, M. D., and Penny, D. (1994) Recovering evolutionary trees under a more realistic model of sequence. Mol. Biol. Evol. 11, 605–612.
Brocchieri, L. (2001) Phylogenetic inferences from molecular sequences: review and critique. Theor. Popul. Biol. 59, 27–40.
Stewart, C.-B. (1993) The powers and pitfalls of parsimony. Nature 361, 603–607.
Attwood, T. K., Beck, M. E., Flower, D. R., Scordis, P., and Selley, J. N. (1998) The PRINTS protein fingerprint database in its fifth year. Nucleic Acids Res. 26, 304–308.
Page, R. D. (1996) TreeView: an application to display phylogenetic trees on personal computers. Comput. Appl. Biosci. 12, 357–358.
Gasteiger, E., Gattiker, A., Hoogland, C., Ivanyi, I., Appel, R. D., and Bairoch A. (2003) ExPASy: the proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Res. 31, 3784–3788.
Rost, B. (1996) PHD: predicting one-dimensional protein structure by profile based neural networks. Methods Enzymol. 266, 525–539.
Eyrich, V. A. and Rost, B. (2003) META-PP: single interface to crucial prediction servers. Nucleic Acids Res. 31, 3308–3310.
Nielsen, H., Engelbrecht, J., Brunak, S., and von Heijne, G. (1997) Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites. Protein Eng. 10, 1–6.
Hansen, J. E., Lund, O., Tolstrup, N, Gooley, A. A., Williams, K. L., and Brunak, S. (1998) NetOglyc: Prediction of mucin type O-glycosylation sites based on sequence context and surface accessibility. Glycoconjugate J. 15, 115–130.
Hansen, J. E., Lund, O., Rapacki, K., and Brunak, S. (1997) O-glycbase version 2.0-A revised database of O-glycosylated proteins. Nucleic Acids Res. 25, 278–282.
Hansen, J. E., Lund, O., Rapacki, K., et al. (1995) Prediction of O-glycosylation of mammalian proteins: specificity patterns of UDP-GalNAc:-polypeptide N-acetylgalactosaminyltransferase. Biochem. J. 308, 801–813.
Blom, N., Gammeltoft, S., and Brunak, S. (1999) Sequence-and structure-based prediction of eukaryotic protein phosphorylation sites. J. Mol. Biol. 294, 1351–1362.
Blom, N., Hansen, J., Blaas, D., and Brunak, S. (1996) Cleavage site analysis in picornaviral polyproteins: Discovering cellular targets by neural networks. Protein Sci. 5, 2203–2216.
Emanuelsson, O., Nielsen, H., and von Heijne, G. (1999) ChloroP, a neural network-based method for predicting chloroplast transit peptides and their cleavage sites. Protein Sci. 8, 978–984.
Cuff, J. A. and Barton, G. J. (1999) Evaluation and improvement of multiple sequence methods for protein secondary structure prediction. Proteins 34, 508–519.
Sonnhammer, E. L. L. von Heijne, G., and 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), pp. 175–182.
von Heijne, G. (1992) Membrane protein structure prediction, hydrophobicity analysis and the positive-inside rule. J. Mol. Biol. 225, 487–494.
Karplus, K., Barrett, C., and Hughey, R. (1998) Hidden markov models for detecting remote protein homologies. Bioinformatics 14, 846–856.
Cserzo, M., Wallin, E., Simon, I., von Heijne, G., and Elofsson, A. (1997) Prediction of transmembrane alpha-helices in procariotic membrane proteins: the dense alignment surface method. Protein Eng. 10, 673–676.
Fischer, D. and Eisenberg, D. A. (1996) Fold recognition using sequence-derived properties. Protein Sci. 5, 947–955.
Elofsson, A., Fischer, D., Rice, D. W., LeGrand, S., and Eisenberg, D. A. (1996) Study of combined structure-sequence profiles. Folding Design 1, 451–461.
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.
Peitsch, M. C. (1995) Protein modelling by E-mail. BioTechnology 13, 658–660.
Peitsch, M. C. (1996) ProMod and Swiss-Model: internet-based tools for automated comparative protein modelling. Biochem. Soc. Trans. 24, 274–279.
Guex, N. and Peitsch, M. C. (1997) SWISS-MODEL and the Swiss-PdbViewer: an environment for comparative protein modelling. Electrophoresis 18, 2714–2723.
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.
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., and Lipman, D. J. (1990) Basic local alignment search tool. J. Mol. Biol. 215, 403–410.
Altschul, S. F. (1991) Amino acid substitution matrices from an information theoretic perspective. J. Mol. Biol. 219, 555–565.
Altschul, S. F. and Gish, W. (1996) Local alignment statistics. Methods Enzymol. 266, 460–480.
Rost, B., Schneider, R., and Sander, C. (1997) Protein fold recognition by prediction-based threading. J. Mol. Biol. 270, 471–480.
Dayhoff, M. O., Barker, W. C., and Hunt, L. T. (1983) Establishing homologies in protein sequences. Methods Enzymol. 91, 524–545.
Henikoff, S. and Henikoff, J. G. (1992) Amino acid substitution matrices from protein blocks. Proc. Natl. Acad. Sci. USA 89, 10,915–10,919.
Pearson, W. R. (1995) Comparison of methods for searching protein sequence databases. Protein Sci. 4, 1145–1160.
Karlin, S. and Altschul, S. E. (1990) Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes. Proc. Natl. Acad. Sci. USA 87, 2264–2268.
Wootton, J. C. (1994) Non-globular domains in protein sequences: automated segmentation using complexity measures. Comput. Chem. 18, 269–285.
Altschul, S. F., Madden, T. L., Schäffer, A. A., et al. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25, 3389–3402.
Pearson, W. R. and Lipman, D. J. (1988) Improved tools for biological sequence comparison. Proc. Natl. Acad. Sci. USA 85, 2444–2448.
Martin, A. C., Orengo, C. A., Hutchinson, E. G., et al. (1998) Protein folds and functions. Structure 6, 875–884.
McGuffin, L. J., Bryson, K., and Jones, D. T. (2001) What are the baselines for protein fold recognition? Bioinformatics 17, 63–72.
Bairoch, A. (1991) PROSITE: a dictionary of sites and patterns in proteins. Nucleic Acids Res. 19, 2241–2245.
Bairoch, A., Bucher, P., and Hofmann, K. (1997) The PROSITE database, its status in 1997. Nucleic Acids Res. 25, 217–221.
Bucher, P., Karplus, K., Moeri, N., and Hofmann, K. (1996) A flexible motif search technique based on generalized profiles. Comput. Chem. 20, 3–23.
Sonnhammer, E. L. and Kahn, D. (1994) Modular arrangement of proteins as inferred from analysis of homology. Protein Sci. 3, 482–492.
Corpet, F., Gouzy, J., and Kahn, D. (1998) The ProDom database of protein domain families. Nucleic Acids Res. 26, 323–326.
Sonnhammer, E. L., Eddy, S. R., and Durbin, R. (1997) Pfam: a comprehensive database of protein domain families based on seed alignments. Proteins 28, 405–420.
Bateman, A., Birney, E., Cerruti, L., et al. (2002) The Pfam protein families database. Nucleic Acids Res. 30, 276–280.
Apweiler, R., Attwood, T. K., 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.
Mulder, N. J., Apweiler, R., Attwood, T. K., et al. (2003) The InterPro Database, 2003 brings increased coverage and new features. Nucleic Acids Res. 31, 315–8.
Rawlings, N. D., O’Brien, E., and Barrett, A.J. (2002) MEROPS: the protease database. Nucleic Acids Res. 30, 343–346.
Storm, C. E. and Sonnhammer, E. L. (2001) NIFAS: visual analysis of domain evolution in proteins. Bioinformatics 17, 343–348.
Schultz, J., Milpetz, F., Bork, P., and Ponting, C. P. (1998) SMART, a simple modular architecture research tool: identification of signaling domains. Proc. Natl. Acad. Sci. USA 95, 5857–5864.
Schultz, J., Copley, R. R., Doerks, T., Ponting, C. P., and Bork, P. (2000) SMART: a web-based tool for the study of genetically mobile domains. Nucleic Acids Res. 28, 231–234.
Letunic, I., Goodstadt, L., Dickens, N. J., et al. (2002) Recent improvements to the SMART domain-based sequence annotation resource. Nucleic Acids Res. 30, 242–244.
Pietrokovski, S., Henikoff, J.G. and Henikoff, S, (1996) The Blocks database-a system for protein classification. Nucleic Acids Res. 24, 197–200.
Attwood, T. K., Flower, D. R., Lewis, A. P., et al. (1999) PRINTS prepares for the new millennium. Nucleic Acids Res. 27, 220–225.
Silverstein, K. A., Shoop, E., Johnson, J. E., and Retzel, E. F. (2001) MetaFam: a unified classification of protein families. I. Overview and statistics. Bioinformatics 17, 249–261.
Yuan, Y. P., Eulenstein, O., Vingron, M., and Bork, P. (1998) Towards detection of orthologues in sequence databases. Bioinformatics 14, 285–289.
Bernstein, F. C., Koetzle, T. F., Williams, G. J., et al. (1977) The Protein Data Bank. A computerbased archival file for macromolecular structures. Eur. J. Biochem. 80, 319–324.
Berman, H. M., Westbrook, J., Feng, Z., et al. (2000) The Protein Data Bank. Nucleic Acids Res. 28, 235–242.
Murzin, A.G., Brenner, S. E., Hubbard, T., and Chothia, C. (1995) SCOP: a structural classification of proteins database for the investigation of sequences and structures. J. Mol. Biol. 247, 536–540.
Orengo, C. A., Michie, A. D., Jones, S., Jones, D. T., Swindells, M. B., and Thornton, J. M. (1997) CATH-a Hierarchic classification of protein domain structures. Structure 5, 1093–1108.
Pearl, F. M. G, Lee, D., Bray, J. E, Sillitoe, I., Todd, A. E., Harrison, A. P., Thornton, J. M., and Orengo, C.A. (2000) Assigning genomic sequences to CATH. Nucleic Acids Res. 28, 277–282.
Peitsch, M. C. and 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.
Schwede, T., Kopp, J., Guex, N., and Peitsch, M. C. (2003) SWISS-MODEL: an automated protein homology-modeling server. Nucleic Acids Res. 31, 3381–3385.
Guex, N. and Peitsch, M. C. (1997) SWISS-MODEL and the Swiss-PdbViewer: an environment for comparative protein modeling. Electrophoresis 18, 2714–2723.
Combet, C., Jambon, M., Deleage, G., and Geourjon, C. (2002) Geno3D: automatic comparative molecular modelling of protein. Bioinformatics 18, 213–214.
Lambert, C., Leonard, N., De Bolle, X., and Depiereux, E. (2002) ESyPred3D: prediction of proteins 3D structures. Bioinformatics 18, 1250–1256.
Bader, G. D., Betel, D., and Hogue, C. W. (2003) BIND: the Biomolecular Interaction Network Database. Nucleic Acids Res. 31, 248–250.
Xenarios, I., Rice, D. W., Salwinski, L., Baron, M. K., Marcotte, E. M., and Eisenberg, D. (2000) DIP: The Database of Interacting Proteins. Nucleic Acids Res. 28, 289–291.
Levinthal, C., Wodak, S. J., Kahn, P., and Dadivanian, A. K. (1975) Hemoglobin interaction in sickle cell fibers. I. Theoretical approaches to the molecular contacts. Proc. Natl. Acad. Sci. USA 72, 1330–1334.
Wodak, S. J. and Janin, J. (1978) Computer analysis of protein-protein interaction. J. Mol. Biol. 124, 323–342.
Janin, J., Henrick, K., Moult, J., et al. (2003) CAPRI: a Critical Assessment of PRedicted Interactions. Proteins 52, 2–9.
Taylor, R. D., Jewsbury, P. J., and Essex, J. W. (2002) A review of protein-small molecule docking methods. J. Comput. Aided Mol. Des. 16, 151–166.
Read, T. D., Peterson, S. N., Tourasse, N., et al. (2003) The genome sequence of Bacillus anthracis Ames and comparison to closely related bacteria. Nature 423, 81–86.
Ivanova, N., Sorokin, A., Anderson, I., et al. (2003) Genome sequence of Bacillus cereus and comparative analysis with Bacillus anthracis. Nature 423, 87–91.
Smith, D. R. (1996) Microbial pathogen genomes-new strategies for identifying therapeutics and vaccine targets. Trends Biotechnol. 14, 290–293.
Tatusov, R. L., Koonin, E. V., and Lipman, D. J. (1997) A genomic perspective on protein families. Science 278, 631–637.
Tatusov, R. L., Natale, D. A., Garkavtsev, I. V., et al. (2001) The COG database: new developments in phylogenetic classification of proteins from complete genomes. Nucleic Acids Res. 29, 22–28.
Wheeler, D. L., Church, D. M., Federhen, S., et al. (2003) Database resources of the National Center for Biotechnology. Nucleic Acids Res. 31, 28–33.
Edgar, R., Domrachev, M., and Lash, A.E. (2002) Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 30, 207–210.
Rehm, B. H. A. and Reinecke, F. (2004) Evaluation of proteomic techniques: applications and potential. Curr. Proteomics 1, 103–111.
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Rehm, B.H.A., Reinecke, F. (2005). Bioinformatic Tools for Gene and Protein Sequence Analysis. In: Walker, J.M., Rapley, R. (eds) Medical Biomethods Handbook. Springer Protocols Handbooks. Humana Press. https://doi.org/10.1385/1-59259-870-6:387
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