Computational Regulatory Genomics

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• Evidence-ranked motif identification

Evidence-ranked motif identification

S. Georgiev,  A. Boyle,  K. Jayasurya,  X. Ding,  S. Mukherjee,  Uwe Ohler 
Genome Biol. 2010 11 2 R19 PubMed Central   DOI   PubMed  

Abstract

cERMIT is a computationally efficient motif discovery tool based on analyzing genome-wide quantitative regulatory evidence. Instead of pre-selecting promising candidate sequences, it utilizes information across all sequence regions to search for high-scoring motifs. We apply cERMIT on a range of direct binding and overexpression datasets; it substantially outperforms state-of-the-art approaches on curated ChIP-chip datasets, and easily scales to current mammalian ChIP-seq experiments with data on thousands of non-coding regions.

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