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De novo motif finding tools such as MEME [44] and MDScan [45] can be used for the transcription factors whose binding site consensuses are less well documented.
The algorithm is benchmarked against popular motif finding tools and demonstrates greater performance.
Recent motif finding tools facilitate the motif detection by providing user-friendly Web interface.
CompleteMOTIF incorporated three existing motif finding tools into a Web tool.
Thus, we looked for similarities between these motifs reported by different motif finding tools.
However, it combines three existing motif finding tools for maximizing the chance obtaining true motifs.
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In contrast to the motif detection tools MAVisto [ 61] and Mfinder [ 36]), our implementation in Prolog and the FANMOD [ 62] motif finding tool are able to find any annotated network pattern consisting of any number of nodes and edges.
MEME is a de novo motif finding tool, which was designed for finding un-gapped motifs in unaligned DNA or protein sequences.
When using the PRIMA motif finding tool [ 35], six subnetworks showed significant enrichment (p < 10-5) for at least one TF (Table 2).
Thus our algorithm has achieved rather high prediction sensitivity even only using these limited 168 datasets, in particular when a putative CRE can be located in the CRMs by a motif finding tool.
The web tool is based on our previous ChIPMotifs program which is a de novo motif finding tool developed for ChIP-based high-throughput data and incorporated various ab initio motif discovery tools such as MEME, MaMF, Weeder and optimized the significance of the detected motifs by using a bootstrap resampling statistic method and a Fisher test.
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