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GIMSAN: a Gibbs motif finder with significance analysis

2008; Oxford University Press; Volume: 24; Issue: 19 Linguagem: Inglês

10.1093/bioinformatics/btn408

1367-4811

Patrick P. Ng, Uri Keich,

Machine Learning in Materials Science

Abstract Summary: We present GIMSAN (GIbbsMarkov with Significance ANalysis): a novel tool for de novo motif finding. GIMSAN combines GibbsMarkov, our variant of the Gibbs Sampler, described here for the first time, with our recently introduced significance analysis. Availability: GIMSAN is currently available as a web application and a stand-alone application on Unix and PBS (Portable Batch System) cluster through links from http://www.cs.cornell.edu/~keich. Contact: keich@cs.cornell.edu