Linked Life Data

15351149

Source:http://linkedlifedata.com/resource/pubmed/id/15351149

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1-3
pubmed:dateCreated
2004-9-7
pubmed:abstractText
We investigate a model of optimal regulation, intended to describe large-scale differential gene expression. Relations between the optimal expression patterns and the function of genes are deduced from an optimality principle: the regulators have to maximise a fitness function which they influence directly via a cost term, and indirectly via their control on important cell variables, such as metabolic fluxes. According to the model, the optimal linear response to small perturbations reflects the regulators' functions, namely their linear influences on the cell variables. The optimal behaviour can be realised by a linear feedback mechanism. Known or assumed properties of response coefficients lead to predictions about regulation patterns. A symmetry relation predicted for deletion experiments is verified with gene expression data. Where the optimality assumption is valid, our results justify the use of expression data for functional annotation and for pathway reconstruction and suggest the use of linear factor models for the analysis of gene expression data.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
0303-2647
pubmed:author
pubmed:issnType
Print
pubmed:volume
76
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
261-78
pubmed:dateRevised
2008-11-21
pubmed:meshHeading
pubmed:articleTitle
A theory of optimal differential gene expression.
pubmed:affiliation
Berlin Center for Genome Based Bioinformatics, Max Planck Institute for Molecular Genetics, Berlin, Germany. lieberme@molgen.mpg.de
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't, Evaluation Studies, Validation Studies