Motif discovery in heterogeneous sequence data.
This paper introduces the first integrated algorithm designed to discover novel motifs in heterogeneous sequence data, which is comprised of coregulated genes from a single genome together with the orthologs of these genes from other genomes. Results are presented for regulons in yeasts, worms, and mammals.
Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195-2350, USA.
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Prakash
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Blanchette
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Sinha
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Tompa
D000465:Algorithms; D000818:Animals; D001665:Binding Sites / Q000235:genetics; D017173:Caenorhabditis elegans / Q000235:genetics; D019295:Computational Biology; D017238:Genes, Helminth; D005809:Genes, Regulator; D023281:Genomics / Q000706:statistics & numerical data; D008957:Models, Genetic; D017422:Sequence Analysis, DNA / Q000706:statistics & numerical data*