WebMOTIFS: automated discovery, filtering and scoring of DNA sequence motifs using multiple programs and Bayesian approaches. 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.
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References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Comin, Matteo; Verzotto, Davide: Filtering degenerate patterns with application to protein sequence analysis (2013)
- Fu, Bin; Fu, Yunhui; Xue, Yuan: Sublinear time motif discovery from multiple sequences (2013)
- Garcia, Fernando; Lopez, Francisco J.; Cano, Carlos; Blanco, Armando: Fisim: A new similarity measure between transcription factor binding sites based on the fuzzy integral (2009) ioport
- Romer, Katherine A.; Kayombya, Guy-Richard; Fraenkel, Ernest: Webmotifs: Automated discovery, filtering and scoring of DNA sequence motifs using multiple programs and Bayesian approaches. (2007) ioport