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Nucleic Acids Research 2005 33(Web Server Issue):W412-W416; doi:10.1093/nar/gki492
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Article

WordSpy: identifying transcription factor binding motifs by building a dictionary and learning a grammar

Guandong Wang1, Taotao Yu1 and Weixiong Zhang1,2,*

1Department of Computer Science and Engineering, Washington University in Saint Louis Saint Louis, MO 63130, USA 2Department of Genetics, Washington University in Saint Louis Saint Louis, MO 63130, USA

*To whom correspondence should be addressed. Tel: +1 314 935 8788; Fax: +1 314 935 7302; Email: zhang{at}cse.wustl.edu

Received February 14, 2005. Revised April 25, 2005. Accepted April 25, 2005.

Transcription factor (TF) binding sites or motifs (TFBMs) are functional cis-regulatory DNA sequences that play an essential role in gene transcriptional regulation. Although many experimental and computational methods have been developed, finding TFBMs remains a challenging problem. We propose and develop a novel dictionary based motif finding algorithm, which we call WordSpy. One significant feature of WordSpy is the combination of a word counting method and a statistical model which consists of a dictionary of motifs and a grammar specifying their usage. The algorithm is suitable for genome-wide motif finding; it is capable of discovering hundreds of motifs from a large set of promoters in a single run. We further enhance WordSpy by applying gene expression information to separate true TFBMs from spurious ones, and by incorporating negative sequences to identify discriminative motifs. In addition, we also use randomly selected promoters from the genome to evaluate the significance of the discovered motifs. The output from WordSpy consists of an ordered list of putative motifs and a set of regulatory sequences with motif binding sites highlighted. The web server of WordSpy is available at http://cic.cs.wustl.edu/wordspy.


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