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Highly specific protein sequence motifs for genome analysis

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Nevill-Manning, Craig G., Wu, Thomas D., Brutlag, Douglas L.·1998·Proceedings of the National Academy of Sciences

Abstract

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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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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CoChat. (2026). Citation check: Highly specific protein sequence motifs for genome analysis. https://app.cochat.ai/papers/10.1073/pnas.95.11.5865
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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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