12204440

Source:http://linkedlifedata.com/resource/pubmed/id/12204440

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Predicate	Object
rdf:type	pubmed:Citation
lifeskim:mentions	umls-concept:C0014279, umls-concept:C0220905, umls-concept:C0449445, umls-concept:C0679083, umls-concept:C0699794, umls-concept:C1512571, umls-concept:C1517503, umls-concept:C1555029, umls-concept:C1882071, umls-concept:C2603343
pubmed:issue	1-2
pubmed:dateCreated	2002-9-2
pubmed:abstractText	Reverse engineering algorithms (REAs) aim at using gene expression data to reconstruct interactions in regulatory genetic networks. This may help to understand the basis of gene regulation, the core task of functional genomics. Collecting data for a number of environmental conditions is necessary to reengineer even the smallest regulatory networks with reasonable confidence. We systematically tested the requirements for the experimental design necessary for ranking alternative hypotheses about the structure of a given regulatory network. A genetic algorithm (GA) was used to explore the parameter space of a multistage discrete genetic network model with fixed connectivity and number of states per node. Our results show that it is not necessary to determine all parameters of the genetic network in order to rank hypotheses. The ranking process is easier the more experimental environmental conditions are used for the data set. During the ranking, the number of fixed parameters increases with the number of environmental conditions, while some errors in the hypothetical network structure may pass undetected, due to a maintained dynamical behaviour.
pubmed:language	eng
pubmed:journal	http://linkedlifedata.com/resource/pubmed/journal/0430773
pubmed:citationSubset	IM
pubmed:status	MEDLINE
pubmed:issn	0303-2647
pubmed:author	pubmed-author:AnderssonSiv G ESG, pubmed-author:LiljenströmHansH, pubmed-author:RepsilberDirkD
pubmed:issnType	Print
pubmed:volume	66
pubmed:owner	NLM
pubmed:authorsComplete	Y
pubmed:pagination	31-41
pubmed:dateRevised	2006-11-15
pubmed:meshHeading	pubmed-meshheading:12204440-Algorithms, pubmed-meshheading:12204440-Gene Expression Regulation, pubmed-meshheading:12204440-Genetic Engineering, pubmed-meshheading:12204440-Models, Genetic
pubmed:articleTitle	Reverse engineering of regulatory networks: simulation studies on a genetic algorithm approach for ranking hypotheses.
pubmed:affiliation	Institute for Molecular Evolution, Evolutionary Biology Centre of the University of Uppsala, Norbyvägen 18C, Sweden. dirk.repsilber@ebc.uu.se
pubmed:publicationType	Journal Article, Research Support, Non-U.S. Gov't