| pubmed-article:21106131 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:21106131 | lifeskim:mentions | umls-concept:C0086418 | lld:lifeskim |
| pubmed-article:21106131 | lifeskim:mentions | umls-concept:C0868995 | lld:lifeskim |
| pubmed-article:21106131 | lifeskim:mentions | umls-concept:C1325816 | lld:lifeskim |
| pubmed-article:21106131 | pubmed:dateCreated | 2010-11-25 | lld:pubmed |
| pubmed-article:21106131 | pubmed:abstractText | Understanding cellular systems requires the knowledge of a protein's subcellular localization (SCL). Although experimental and predicted data for protein SCL are archived in various databases, SCL prediction remains a non-trivial problem in genome annotation. Current SCL prediction tools use amino-acid sequence features and text mining approaches. A comprehensive analysis of protein SCL in human PPI and metabolic networks for various subcellular compartments is necessary for developing a robust SCL prediction methodology. | lld:pubmed |
| pubmed-article:21106131 | pubmed:language | eng | lld:pubmed |
| pubmed-article:21106131 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:21106131 | pubmed:citationSubset | IM | lld:pubmed |
| pubmed-article:21106131 | pubmed:chemical | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:21106131 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:21106131 | pubmed:issn | 1471-2105 | lld:pubmed |
| pubmed-article:21106131 | pubmed:author | pubmed-author:RanganathanSh... | lld:pubmed |
| pubmed-article:21106131 | pubmed:author | pubmed-author:KumarGauravG | lld:pubmed |
| pubmed-article:21106131 | pubmed:issnType | Electronic | lld:pubmed |
| pubmed-article:21106131 | pubmed:volume | 11 Suppl 7 | lld:pubmed |
| pubmed-article:21106131 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:21106131 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:21106131 | pubmed:pagination | S9 | lld:pubmed |
| pubmed-article:21106131 | pubmed:meshHeading | pubmed-meshheading:21106131... | lld:pubmed |
| pubmed-article:21106131 | pubmed:meshHeading | pubmed-meshheading:21106131... | lld:pubmed |
| pubmed-article:21106131 | pubmed:meshHeading | pubmed-meshheading:21106131... | lld:pubmed |
| pubmed-article:21106131 | pubmed:meshHeading | pubmed-meshheading:21106131... | lld:pubmed |
| pubmed-article:21106131 | pubmed:meshHeading | pubmed-meshheading:21106131... | lld:pubmed |
| pubmed-article:21106131 | pubmed:meshHeading | pubmed-meshheading:21106131... | lld:pubmed |
| pubmed-article:21106131 | pubmed:meshHeading | pubmed-meshheading:21106131... | lld:pubmed |
| pubmed-article:21106131 | pubmed:meshHeading | pubmed-meshheading:21106131... | lld:pubmed |
| pubmed-article:21106131 | pubmed:meshHeading | pubmed-meshheading:21106131... | lld:pubmed |
| pubmed-article:21106131 | pubmed:year | 2010 | lld:pubmed |
| pubmed-article:21106131 | pubmed:articleTitle | Network analysis of human protein location. | lld:pubmed |
| pubmed-article:21106131 | pubmed:affiliation | ARC Centre of Excellence in Bioinformatics and Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney NSW, Australia. gaurav.kumar@mq.edu.au | lld:pubmed |
| pubmed-article:21106131 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:21106131 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
