Linked Life Data

12653656

Source:http://linkedlifedata.com/resource/pubmed/id/12653656

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2003-3-25
pubmed:abstractText
Application of statistical genetics approaches to variations in mRNA transcript abundances in segregating populations can be used to identify genes and pathways associated with common human diseases. The combination of this genetic information with gene expression and clinical trait data can also be used to identify subtypes of a disease and the genetic loci specific to each subtype. Here we highlight results from some of our recent work in this area and further explore the many possibilities that exist in employing a more comprehensive genetics and functional genomics approach to the functional annotation of genomes, and in applying such methods to the validation of targets for complex traits in the drug discovery process.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0300-5127
pubmed:author
pubmed:issnType
Print
pubmed:volume
31
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
437-43
pubmed:dateRevised
2010-11-18
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
A new paradigm for drug discovery: integrating clinical, genetic, genomic and molecular phenotype data to identify drug targets.
pubmed:affiliation
Rosetta Inpharmatics LLC, 12040 115th Avenue N.E., Kirkland, WA 98034, U.S.A. eric_schadt@merck.com
pubmed:publicationType
Journal Article, Review