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Journal of Information Science and Engineering, Vol. 26 No. 6, pp. 2309-2318 (November 2010)

A Greedy Two-stage Gibbs Sampling Method for Motif Discovery in Biological Sequences*

LI-FANG LIU AND LI-CHENG JIAO+
School of Computer Science and Technology
+Institute of Intelligent Information Processing
Xidian University
Xi'an, 710071 P.R. China

For the motif discovery problem of DNA or protein sequences, a greedy two-stage Gibbs sampling algorithm is presented, and the related software package is called Greedy Motifsam. Based on position weight matrix (PWM) motif model, a greedy strategy for choosing the initial parameters of PWM is employed. Two sampling methods, site sampler and motif sampler, are used. Site sampler is used to find one occurrence per sequence of the motif in the dataset. Motif sampler is used to find zero or more non-overlapping occurrences of the motif in each sequence. The algorithm is capable of discovering several different motifs with differing numbers of occurrences in a single dataset. We use the binding sites (motif) information of eukaryotic transcription factors stored in TRANSFAC database to test our methods. The prediction accuracy, scalability and reliability are compared to several other methods. Our proposed method is also illustrated as applied to helix-turn-helix proteins, lipocalins, and prenyltransferases. The Greedy Motifsam software is available at http://lxy.xidian.edu.cn/math/intro/teachers/ qxg/MotifSAM.zip.

Keywords: motif discovery, Gibbs sampling, binding sites, transcription factors, biological sequences, greedy motifSAM

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Received April 30, 2009; revised July 22, 2009; accepted September 3, 2009.
Communicated by Jorng-Tzong Horng.
* This work was supported by the National Natural Science Foundation of China under Grant No. 60705004 and the Fundamental Research Funds for the Central Universities, 2010.