| pubmed-article:20444264 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:20444264 | lifeskim:mentions | umls-concept:C0023185 | lld:lifeskim |
| pubmed-article:20444264 | lifeskim:mentions | umls-concept:C1446409 | lld:lifeskim |
| pubmed-article:20444264 | lifeskim:mentions | umls-concept:C1511726 | lld:lifeskim |
| pubmed-article:20444264 | lifeskim:mentions | umls-concept:C1720950 | lld:lifeskim |
| pubmed-article:20444264 | pubmed:dateCreated | 2010-6-18 | lld:pubmed |
| pubmed-article:20444264 | pubmed:abstractText | Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled as a binary classification problem for each pair of genes. A statistical classifier is trained to recognize the relationships between the activation profiles of gene pairs. This approach has been proven to outperform previous unsupervised methods. However, the supervised approach raises open questions. In particular, although known regulatory connections can safely be assumed to be positive training examples, obtaining negative examples is not straightforward, because definite knowledge is typically not available that a given pair of genes do not interact. | lld:pubmed |
| pubmed-article:20444264 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
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| pubmed-article:20444264 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
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| pubmed-article:20444264 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:20444264 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:20444264 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:20444264 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:20444264 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:20444264 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
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| pubmed-article:20444264 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:20444264 | pubmed:language | eng | lld:pubmed |
| pubmed-article:20444264 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:20444264 | pubmed:citationSubset | IM | lld:pubmed |
| pubmed-article:20444264 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:20444264 | pubmed:issn | 1471-2105 | lld:pubmed |
| pubmed-article:20444264 | pubmed:author | pubmed-author:CeccarelliMic... | lld:pubmed |
| pubmed-article:20444264 | pubmed:author | pubmed-author:ElkanCharlesC | lld:pubmed |
| pubmed-article:20444264 | pubmed:author | pubmed-author:CeruloLuigiL | lld:pubmed |
| pubmed-article:20444264 | pubmed:issnType | Electronic | lld:pubmed |
| pubmed-article:20444264 | pubmed:volume | 11 | lld:pubmed |
| pubmed-article:20444264 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:20444264 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:20444264 | pubmed:pagination | 228 | lld:pubmed |
| pubmed-article:20444264 | pubmed:meshHeading | pubmed-meshheading:20444264... | lld:pubmed |
| pubmed-article:20444264 | pubmed:meshHeading | pubmed-meshheading:20444264... | lld:pubmed |
| pubmed-article:20444264 | pubmed:meshHeading | pubmed-meshheading:20444264... | lld:pubmed |
| pubmed-article:20444264 | pubmed:meshHeading | pubmed-meshheading:20444264... | lld:pubmed |
| pubmed-article:20444264 | pubmed:meshHeading | pubmed-meshheading:20444264... | lld:pubmed |
| pubmed-article:20444264 | pubmed:year | 2010 | lld:pubmed |
| pubmed-article:20444264 | pubmed:articleTitle | Learning gene regulatory networks from only positive and unlabeled data. | lld:pubmed |
| pubmed-article:20444264 | pubmed:affiliation | Department of Biological and Environmental Studies, University of Sannio, Benevento, Italy. lcerulo@unisannio.it | lld:pubmed |
| pubmed-article:20444264 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:20444264 | pubmed:publicationType | Comparative Study | lld:pubmed |
| pubmed-article:20444264 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
| http://linkedlifedata.com/r... | pubmed:referesTo | pubmed-article:20444264 | lld:pubmed |
