WebMOTIFS: automated discovery, filtering and scoring of DNA sequence motifs using multiple programs and Bayesian approaches

• Published in: Nucleic acids research Vol. 35; no. Web Server issue; pp. W217 - W220
• Main Authors: Romer, Katherine A, Kayombya, Guy-Richard, Fraenkel, Ernest
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01-07-2007
• Subjects: Algorithms; Amino Acid Motifs; Animals; Automation; Bayes Theorem; Cluster Analysis; Computational Biology - methods; Conserved Sequence; DNA - chemistry; Gene Expression Profiling - methods; Humans; Mice; Pattern Recognition, Automated; Saccharomyces cerevisiae - genetics; Sequence Alignment; Software
• ISSN: 0305-1048; 1362-4962
• DOI: 10.1093/nar/gkm376

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.