Linked Life Data

20510918

Source:http://linkedlifedata.com/resource/pubmed/id/20510918

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2010-5-31
pubmed:abstractText
Traditionally, research has been reductionist, characterizing the individual components of biological systems. But new technologies have increased the size and scope of biological data, and systems approaches have broadened the view of how these components are interconnected. Here, we discuss how quantitative mapping of genetic interactions enhances our view of biological systems, allowing their deeper interrogation across different biological scales.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
1097-4172
pubmed:author
pubmed:copyrightInfo
Copyright 2010 Elsevier Inc. All rights reserved.
pubmed:issnType
Electronic
pubmed:day
28
pubmed:volume
141
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
739-45
pubmed:dateRevised
2011-3-15
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Quantitative genetic interactions reveal biological modularity.
pubmed:affiliation
Department of Cellular and Molecular Pharmacology, California Institute for Quantitative Biomedical Research, University of California, San Francisco, San Francisco, CA 94158, USA.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural