| pubmed-article:20156354 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:20156354 | lifeskim:mentions | umls-concept:C0020792 | lld:lifeskim |
| pubmed-article:20156354 | lifeskim:mentions | umls-concept:C1514562 | lld:lifeskim |
| pubmed-article:20156354 | pubmed:issue | 2 | lld:pubmed |
| pubmed-article:20156354 | pubmed:dateCreated | 2010-5-20 | lld:pubmed |
| pubmed-article:20156354 | pubmed:abstractText | 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. | lld:pubmed |
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| pubmed-article:20156354 | pubmed:language | eng | lld:pubmed |
| pubmed-article:20156354 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:20156354 | pubmed:citationSubset | IM | lld:pubmed |
| pubmed-article:20156354 | pubmed:chemical | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:20156354 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:20156354 | pubmed:issn | 1465-6914 | lld:pubmed |
| pubmed-article:20156354 | pubmed:author | pubmed-author:MukherjeeSaya... | lld:pubmed |
| pubmed-article:20156354 | pubmed:author | pubmed-author:OhlerUweU | lld:pubmed |
| pubmed-article:20156354 | pubmed:author | pubmed-author:DingXuanX | lld:pubmed |
| pubmed-article:20156354 | pubmed:author | pubmed-author:BoyleAlan PAP | lld:pubmed |
| pubmed-article:20156354 | pubmed:author | pubmed-author:GeorgievStoya... | lld:pubmed |
| pubmed-article:20156354 | pubmed:author | pubmed-author:JayasuryaKart... | lld:pubmed |
| pubmed-article:20156354 | pubmed:issnType | Electronic | lld:pubmed |
| pubmed-article:20156354 | pubmed:volume | 11 | lld:pubmed |
| pubmed-article:20156354 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:20156354 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:20156354 | pubmed:pagination | R19 | lld:pubmed |
| pubmed-article:20156354 | pubmed:dateRevised | 2010-9-28 | lld:pubmed |
| pubmed-article:20156354 | pubmed:meshHeading | pubmed-meshheading:20156354... | lld:pubmed |
| pubmed-article:20156354 | pubmed:meshHeading | pubmed-meshheading:20156354... | lld:pubmed |
| pubmed-article:20156354 | pubmed:meshHeading | pubmed-meshheading:20156354... | lld:pubmed |
| pubmed-article:20156354 | pubmed:meshHeading | pubmed-meshheading:20156354... | lld:pubmed |
| pubmed-article:20156354 | pubmed:meshHeading | pubmed-meshheading:20156354... | lld:pubmed |
| pubmed-article:20156354 | pubmed:meshHeading | pubmed-meshheading:20156354... | lld:pubmed |
| pubmed-article:20156354 | pubmed:meshHeading | pubmed-meshheading:20156354... | lld:pubmed |
| pubmed-article:20156354 | pubmed:meshHeading | pubmed-meshheading:20156354... | lld:pubmed |
| pubmed-article:20156354 | pubmed:meshHeading | pubmed-meshheading:20156354... | lld:pubmed |
| pubmed-article:20156354 | pubmed:year | 2010 | lld:pubmed |
| pubmed-article:20156354 | pubmed:articleTitle | Evidence-ranked motif identification. | lld:pubmed |
| pubmed-article:20156354 | pubmed:affiliation | Program for Computational Biology and Bioinformatics, Duke University, 102 North Building, Durham, NC 27708, USA. | lld:pubmed |
| pubmed-article:20156354 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:20156354 | pubmed:publicationType | Research Support, U.S. Gov't, Non-P.H.S. | lld:pubmed |
| pubmed-article:20156354 | pubmed:publicationType | Research Support, N.I.H., Extramural | lld:pubmed |
| http://linkedlifedata.com/r... | pubmed:referesTo | pubmed-article:20156354 | lld:pubmed |
