Linked Life Data

15556037

Source:http://linkedlifedata.com/resource/pubmed/id/15556037

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2004-11-23
pubmed:abstractText
A major objective in post-genome research is to fully understand the transcriptional control of each gene and the targets of each transcription factor. In yeast, large-scale experimental and computational approaches have been applied to identify co-regulated genes, cis regulatory elements, and transcription factor DNA binding sites in vivo. Methods for modeling and predicting system behavior, and for reconciling discrepancies among data types, are being explored. The results indicate that a complete and comprehensive yeast transcriptional network will ultimately be achieved.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
1369-5274
pubmed:author
pubmed:issnType
Print
pubmed:volume
7
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
638-46
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
Transcriptional networks: reverse-engineering gene regulation on a global scale.
pubmed:affiliation
Banting and Best Department of Medical Research, University of Toronto, 112 College Street, Room 307, Toronto, Ontario M5G 1L6, Canada.
pubmed:publicationType
Journal Article, Review, Research Support, Non-U.S. Gov't