Bioinformatics Advance Access published online on February 2, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl037
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1 UCSF Cancer Research Institute and Comprehensive Cancer Center, University of California, San Francisco
* To whom correspondence should be addressed.
Motivation: We present a novel algorithm, MaMF, for identifying transcription factor (TF) binding site motifs. The method is deterministic and depends on an indexing technique to optimize the search process. On common yeast data sets, MaMF performs competitively with other methods. We also present results on a challenging group of eight sets of human genes known to be responsive to a diverse group of TFs. In every case, MaMF finds the annotated motif among the top scoring putative motifs. We compared MaMF against other motif finders on a larger human group of 21 gene sets and found that MaMF performs better than other algorithms. We analyzed the remaining high scoring motifs and show that many correspond to other TFs that are known to co-occur with the annotated TF motifs. The significant and frequent presence of co-occurring transcription factor binding sites explains in part the difficulty of human motif finding. MaMF is a very fast algorithm, suitable for application to large numbers of interesting gene sets. Availability: The software is available for academic research use free of charge by email request. Supplemental Information: Data comprising the benchmarks used in the paper may be downloaded from http://www.jainlab.org/downloads.html.
Received October 14, 2005
Revised December 1, 2005
Accepted February 1, 2006
Article
A deterministic motif finding algorithm with application to the human genome
Lawrence S. Hon 1
and
Ajay N. Jain 1 *
Ajay N. Jain, E-mail: ajain{at}jainlab.org
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Abstract
Associate Editor: Nikolaus Rajewsky
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