| pubmed-article:21494644 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:21494644 | lifeskim:mentions | umls-concept:C0011570 | lld:lifeskim |
| pubmed-article:21494644 | lifeskim:mentions | umls-concept:C1511726 | lld:lifeskim |
| pubmed-article:21494644 | lifeskim:mentions | umls-concept:C0220825 | lld:lifeskim |
| pubmed-article:21494644 | lifeskim:mentions | umls-concept:C0035201 | lld:lifeskim |
| pubmed-article:21494644 | lifeskim:mentions | umls-concept:C1332838 | lld:lifeskim |
| pubmed-article:21494644 | lifeskim:mentions | umls-concept:C2347299 | lld:lifeskim |
| pubmed-article:21494644 | pubmed:issue | 4 | lld:pubmed |
| pubmed-article:21494644 | pubmed:dateCreated | 2011-4-15 | lld:pubmed |
| pubmed-article:21494644 | pubmed:abstractText | Large scale and individual genetic studies have suggested numerous susceptible genes for depression in the past decade without conclusive results. There is a strong need to review and integrate multi-dimensional data for follow up validation. The present study aimed to apply prioritization procedures to build-up an evidence-based candidate genes dataset for depression. | lld:pubmed |
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| pubmed-article:21494644 | pubmed:language | eng | lld:pubmed |
| pubmed-article:21494644 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:21494644 | pubmed:citationSubset | IM | lld:pubmed |
| pubmed-article:21494644 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:21494644 | pubmed:issn | 1932-6203 | lld:pubmed |
| pubmed-article:21494644 | pubmed:author | pubmed-author:KuoPo-HsiuPH | lld:pubmed |
| pubmed-article:21494644 | pubmed:author | pubmed-author:ZhaoZhongming... | lld:pubmed |
| pubmed-article:21494644 | pubmed:author | pubmed-author:KaoChung-Feng... | lld:pubmed |
| pubmed-article:21494644 | pubmed:author | pubmed-author:FangYu-ShengY... | lld:pubmed |
| pubmed-article:21494644 | pubmed:issnType | Electronic | lld:pubmed |
| pubmed-article:21494644 | pubmed:volume | 6 | lld:pubmed |
| pubmed-article:21494644 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:21494644 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:21494644 | pubmed:pagination | e18696 | lld:pubmed |
| pubmed-article:21494644 | pubmed:meshHeading | pubmed-meshheading:21494644... | lld:pubmed |
| pubmed-article:21494644 | pubmed:meshHeading | pubmed-meshheading:21494644... | lld:pubmed |
| pubmed-article:21494644 | pubmed:meshHeading | pubmed-meshheading:21494644... | lld:pubmed |
| pubmed-article:21494644 | pubmed:meshHeading | pubmed-meshheading:21494644... | lld:pubmed |
| pubmed-article:21494644 | pubmed:meshHeading | pubmed-meshheading:21494644... | lld:pubmed |
| pubmed-article:21494644 | pubmed:meshHeading | pubmed-meshheading:21494644... | lld:pubmed |
| pubmed-article:21494644 | pubmed:year | 2011 | lld:pubmed |
| pubmed-article:21494644 | pubmed:articleTitle | Prioritization and evaluation of depression candidate genes by combining multidimensional data resources. | lld:pubmed |
| pubmed-article:21494644 | pubmed:affiliation | Department of Public Health and Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan. | lld:pubmed |
| pubmed-article:21494644 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:21494644 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
