Evidence-ranked motif identification.
Data(s) |
2010
|
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Identificador |
http://www.ncbi.nlm.nih.gov/pubmed/20156354 gb-2010-11-2-r19 Genome Biol, 2010, 11 (2), pp. R19 - ? http://hdl.handle.net/10161/10579 1474-760X |
Idioma(s) |
ENG en_US |
Relação |
Genome Biol 10.1186/gb-2010-11-2-r19 http://hdl.handle.net/10161/4393 10161/4393 Genome biology |
Tipo |
Journal Article |
Cobertura |
England |
Resumo |
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. |
Formato |
R19 - ? |
Palavras-Chave | #Animals #Computational Biology #DNA, Fungal #Genome, Human #Genome-Wide Association Study #Humans #Mice #Oligonucleotide Array Sequence Analysis #Sequence Analysis, DNA |