Open AccessCombinatorial motif analysis and hypothesis generation on a genomic scale
Author(s) -
YuhJyh Hu,
Suzanne Sandmeyer,
Calvin S. McLaughlin,
Dennis Kibler
Publication year - 2000
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/16.3.222
Subject(s) - motif (music) , computer science , computational biology , executable , sequence motif , biology , gene , genetics , programming language , physics , acoustics
Computer-assisted methods are essential for the analysis of biosequences. Gene activity is regulated in part by the binding of regulatory molecules (transcription factors) to combinations of short motifs. The goal of our analysis is the development of algorithms to identify regulatory motifs and to predict the activity of combinations of those motifs.
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