WebMOTIFS: automated discovery, filtering and scoring of DNA sequence motifs using multiple programs and Bayesian approaches
Name
Romer-2007-WebMOTIFS.pdf
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1.72 MB
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Adobe PDF
Checksum (MD5)
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Author(s)
Romer, Katherine A.
Kayombya, Guy-Richard
Fraenkel, Ernest
Date Issued
June 2007
Journal
Nucleic Acids Research
Publisher
Oxford University Press (OUP)
Citation
Romer, K. A., G.-R. Kayombya, and E. Fraenkel. “WebMOTIFS: Automated Discovery, Filtering and Scoring of DNA Sequence Motifs Using Multiple Programs and Bayesian Approaches.” Nucleic Acids Research 35.Web Server (2007): W217–W220. Web. 25 May 2012.
Version
Final published version
Abstract
WebMOTIFS provides a web interface that facilitates the discovery and analysis of DNA-sequence motifs. Several studies have shown that the accuracy of motif discovery can be significantly improved by using multiple de novo motif discovery programs and using randomized control calculations to identify the most significant motifs or by using Bayesian approaches. WebMOTIFS makes it easy to apply these strategies. Using a single submission form, users can run several motif discovery programs and score, cluster and visualize the results. In addition, the Bayesian motif discovery program THEME can be used to determine the class of transcription factors that is most likely to regulate a set of sequences. Input can be provided as a list of gene or probe identifiers. Used with the default settings, WebMOTIFS accurately identifies biologically relevant motifs from diverse data in several species. WebMOTIFS is freely available at http://fraenkel.mit.edu/webmotifs.
MIT Department
Massachusetts Institute of Technology. Computational and Systems Biology Program
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution Non-Commercial
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1093/nar/gkm376
