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PMID: 12386004 Published · ppublish English Evaluation Study Journal Article Research Support, Non-U.S. Gov't

Building and analysing genome-wide gene disruption networks.

Bioinformatics (Oxford, England) ·Vol. 18 Suppl 2 ·2002-00-00 ·Pages S202-10

Rung J, Schlitt T, Brazma A, Freivalds K, Vilo J

Abstract

Microarray experiments comparing expression levels of all genes in yeast for hundreds of mutants allow us to examine properties of gene regulatory networks on a genomic scale. We can investigate questions such as network modularity, connectivity, and look for genes with particular roles in the network structure. We have built genome-wide disruption networks for yeast, using a representation of gene expression data as directed labelled graphs. Nodes represent genes and arcs connect nodes if the disruption of the source gene significantly alters the expression of the target gene. We are interested in features of the resulting disruption networks that are robust over a range of significance cutoffs. The networks show a significant overlap with analogous networks constructed from scientific literature. In disruption networks the number of arcs adjacent to different nodes are distributed roughly according to a power-law, like in many complex systems where the robustness against perturbations is important. The networks are dominated by a single large component and do not have an obvious modular structure. Genes with the highest outdegrees often encode proteins with regulatory functions, whereas genes with the highest indegrees are predominantly involved in metabolism. The local structure of the networks is meaningful, genes involved in the same cellular processes are close together in the network. http://www.ebi.ac.uk/microarray/networks

MeSH Terms
Chromosome Mapping/methods Gene Expression Profiling/methods Gene Expression Regulation, Fungal/physiology Gene Silencing Genome, Fungal Models, Biological Oligonucleotide Array Sequence Analysis/methods Protein Interaction Mapping/methods Proteome/genetics,metabolism Saccharomyces cerevisiae/physiology Saccharomyces cerevisiae Proteins/genetics,metabolism Signal Transduction/physiology
Chemicals
Proteome Saccharomyces cerevisiae Proteins
Authors & Affiliations
5 authors, click to expand affiliations / ORCID
Rung J
European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.
Schlitt T
Brazma A
Freivalds K
Vilo J
Article Info
Journal
Bioinformatics (Oxford, England)
Abbr.
Bioinformatics
ISSN
1367-4803
Published
2002-00-00
Pages
S202-10
Language
English
Region
England
NLM ID
9808944
Subset
IM
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