Linked Life Data

21699718

Source:http://linkedlifedata.com/resource/pubmed/id/21699718

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2011-7-22
pubmed:abstractText
Semantic Web Technology (SWT) makes it possible to integrate and search the large volume of life science datasets in the public domain, as demonstrated by well-known linked data projects such as LODD, Bio2RDF, and Chem2Bio2RDF. Integration of these sets creates large networks of information. We have previously described a tool called WENDI for aggregating information pertaining to new chemical compounds, effectively creating evidence paths relating the compounds to genes, diseases and so on. In this paper we examine the utility of automatically inferring new compound-disease associations (and thus new links in the network) based on semantically marked-up versions of these evidence paths, rule-sets and inference engines.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1471-2105
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
12
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
256
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Semantic inference using chemogenomics data for drug discovery.
pubmed:affiliation
School of Informatics and Computing, Indiana University, Bloomington, USA. qianzhu@indiana.edu
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't