Computational analysis of the synergy among multiple interacting genes

Diseases such as cancer are often related to collaborative effects involving interactions of multiple genes within complex pathways, or to combinations of multiple SNPs. To understand the structure of such mechanisms, it is helpful to analyze genes in terms of the purely cooperative, as opposed to i...

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Bibliographic Details
Published in:Molecular systems biology 2007, Vol.3 (1), p.83-n/a
Main Author: Anastassiou, Dimitris
Format: Article
Language:English
Subjects:
Biology
Cancer
Computational Biology - methods
Computer applications
Decomposition
Gene expression
Gene Expression Profiling
gene modules
Gene Regulatory Networks
Genes
Genetic Predisposition to Disease
Genotype & phenotype
Humans
Information theory
Knowledge
microarray analysis
Neurosciences
pathways
Phenotypes
Polymorphism, Single Nucleotide
Review
Single-nucleotide polymorphism
SNP data
Software
synergy
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Summary:Diseases such as cancer are often related to collaborative effects involving interactions of multiple genes within complex pathways, or to combinations of multiple SNPs. To understand the structure of such mechanisms, it is helpful to analyze genes in terms of the purely cooperative, as opposed to independent, nature of their contributions towards a phenotype. Here, we present an information‐theoretic analysis that provides a quantitative measure of the multivariate synergy and decomposes sets of genes into submodules each of which contains synergistically interacting genes. When the resulting computational tools are used for the analysis of gene expression or SNP data, this systems‐based methodology provides insight into the biological mechanisms responsible for disease.
ISSN:1744-4292
1744-4292
DOI:10.1038/msb4100124