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Bioinformatics Advance Access originally published online on October 5, 2007
Bioinformatics 2007 23(21):2823-2828; doi:10.1093/bioinformatics/btm473
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

OSCAR: One-class SVM for accurate recognition of cis-elements

Bo Jiang 1, Michael Q. Zhang 1,2 and Xuegong Zhang 1,*

1MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China and 2Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11274, USA

*To whom correspondence should be addressed.


  Abstract

Motivation: Traditional methods to identify potential binding sites of known transcription factors still suffer from large number of false predictions. They mostly use sequence information in a position-specific manner and neglect other types of information hidden in the proximal promoter regions. Recent biological and computational researches, however, suggest that there exist not only locational preferences of binding, but also correlations between transcription factors.

Results: In this article, we propose a novel approach, OSCAR, which utilizes one-class SVM algorithms, and incorporates multiple factors to aid the recognition of transcription factor binding sites. Using both synthetic and real data, we find that our method outperforms existing algorithms, especially in the high sensitivity region. The performance of our method can be further improved by taking into account locational preference of binding events. By testing on experimentally-verified binding sites of GATA and HNF transcription factor families, we show that our algorithm can infer the true co-occurring motif pairs accurately, and by considering the co-occurrences of correlated motifs, we not only filter out false predictions, but also increase the sensitivity.

Availability: An online server based on OSCAR is available at http://bioinfo.au.tsinghua.edu.cn/oscar.

Contact: zhangxg{at}tsinghua.edu.cn

Associate Editor: Alex Bateman

Received on April 25, 2007; revised on August 29, 2007; accepted on September 11, 2007

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