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Highly specific protein sequence motifs for genome analysis
Open accessAbstract
We present a method for discovering conserved sequence motifs from families of aligned protein sequences. The method has been implemented as a computer program called emotif ( http://motif.stanford.edu/emotif ). Given an aligned set of protein sequences, emotif generates a set of motifs with a wide range of specificities and sensitivities. emotif also can generate motifs that describe possible subfamilies of a protein superfamily. A disjunction of such motifs often can represent the entire superfamily with high specificity and sensitivity. We have used emotif to generate sets of motifs from all 7,000 protein alignments in the blocks and prints databases. The resulting database, called identify ( http://motif.stanford.edu/identify ), contains more than 50,000 motifs. For each alignment, the database contains several motifs having a probability of matching a false positive that range from 10 −10 to 10 −5 . Highly specific motifs are well suited for searching entire proteomes, while generating very few false predictions. identify assigns biological functions to 25–30% of all proteins encoded by the Saccharomyces cerevisiae genome and by several bacterial genomes. In particular, identify assigned functions to 172 of proteins of unknown function in the yeast genome.
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Cited by
The SWISS-PROT protein sequence data bank and its supplement TrEMBL in 1998
Bairoch, A. (1998) · Nucleic Acids Research · doi:10.1093/nar/26.1.38 · Cited by 3,280
Apweiler, R. (2001) · Nucleic Acids Research · doi:10.1093/nar/29.1.37 · Cited by 1,079
Oelkers, P., Behari, A., Cromley, D., Billheimer, J. T., & Sturley, S. L. (1998) · Journal of Biological Chemistry · doi:10.1074/jbc.273.41.26765 · Cited by 373
Understanding eukaryotic linear motifs and their role in cell signaling and regulation
Diella, F. (2008) · Frontiers in Bioscience · doi:10.2741/3175 · Cited by 340
Multiobjective Optimization in Bioinformatics and Computational Biology
Handl, J., Kell, D. B., & Knowles, J. (2007) · IEEE/ACM Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2007.070203 · Cited by 308
Metadata
- Authors
- Nevill-Manning, C. G., Wu, T. D., & Brutlag, D. L.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 1998-05-26
- Volume
- 95
- Issue
- 11
- Pages
- 5865-5871
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2165979580
- Cited by
- 196
- References
- 0
- FWCI
- 7.09
- Type
- journal article
- Language
- en
- Open access
- green
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- Nevill-Manning, C. G., Wu, T. D., & Brutlag, D. L. (1998). Highly specific protein sequence motifs for genome analysis. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.95.11.5865
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