Linked Life Data

15708532

Source:http://linkedlifedata.com/resource/pubmed/id/15708532

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2005-2-14
pubmed:abstractText
Relevance of a drug target for a disease is often inferred with strong belief but fragile evidence. Here, a program for early identification of human disease-specific drug targets using high-throughput genetic associations is described. Large numbers of well-characterized patients (>1000) and matched controls are screened for genetic associations using several thousand (>7000) single nucleotide polymorphisms from more than 1500 genes. The genes were selected because they are members of target classes for which there are precedents for high-throughput chemical screening technology. This review summarizes the methods and intensive data analyses leading to target gene identification for type 2 diabetes mellitus, including the statistical permutation methodology used to correct for many variables.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
1359-6446
pubmed:author
pubmed:issnType
Print
pubmed:day
1
pubmed:volume
10
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
177-89
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Disease-specific target selection: a critical first step down the right road.
pubmed:affiliation
GlaxoSmithKline R&D, Research Triangle Park, NC 27709, USA. allen.d.roses@gsk.com
pubmed:publicationType
Journal Article, Review, Research Support, Non-U.S. Gov't