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Nevill-Manning, C. G., Wu, T. D. and Brutlag, D. L. (1998). Highly Specific Protein Sequence Motifs for Genome Analysis. Proc. Natl. Acad. Sci. USA, 95, In press.

Highly Specific Protein Sequence Motifs for Genome Analysis.

Nevill-Manning, C. G, Wu, T. D., Brutlag, D. L.

Department of Biochemistry, Stanford University School of Medicine, Stanford CA, 94305-5307

We present a novel 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 can also generate motifs that describe possible subfamilies of a protein superfamily. A disjunction of such motifs can often 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 over 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 to 30% of all the proteins encoded by the Saccharomyces cerevisiae genome and by several bacterial genomes. In particular, IDENTIFY assigned functions to 172 of the proteins of unknown function in the yeast genome.

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