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The various motif discovery programs have significant limitations.
The main problem with all the current motif discovery programs is their low accuracy.
The justification for combining multiple motif discovery programs is described in Additional file 1.
One of the first ensemble algorithms was the BEST program [ 14] which combined the advantages of three motif discovery programs.
However, each of the three standalone motif discovery programs appeared to identify different sets of motifs (see Additional file 3).
Similar results were obtained using other de novo motif discovery programs such as NHR-Scan [ 5] and W-ChIPMotifs [ 35].
Similar(35)
A motif discovery program, cis-regulatory element annotation system (CEAS) (http://ceas.cbi.pku.edu.cn) (Ji et al. 2006), was also performed to obtain the enriched transcription factor motifs located in ChIPseq-identified GBRs. ChIPseq-identified GBRs
An independent reanalysis of the identical ChIP-seq data set using the popular motif discovery program MEME [25] on a very similar set of 'high-coverage' binding sequences [7] reports two motifs named M1 and M2.
Greater confidence was reposed in strongly related motif-sets identified by more than one motif discovery program.
We have chosen to use MEME, which is a publicly available motif discovery program [ 12] supporting an expectation maximization algorithm.
Each motif discovery program can then be compared based on the rate of true and false predictions.
Related(15)
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