Network-based global inference of human disease genes

Wu, X., Jiang, R., Zhang, M. Q., Li, S. (2008) Network-based global inference of human disease genes. Mol Syst Biol, 4. p. 189.

Abstract

Deciphering the genetic basis of human diseases is an important goal of biomedical research. On the basis of the assumption that phenotypically similar diseases are caused by functionally related genes, we propose a computational framework that integrates human protein-protein interactions, disease phenotype similarities, and known gene-phenotype associations to capture the complex relationships between phenotypes and genotypes. We develop a tool named CIPHER to predict and prioritize disease genes, and we show that the global concordance between the human protein network and the phenotype network reliably predicts disease genes. Our method is applicable to genetically uncharacterized phenotypes, effective in the genome-wide scan of disease genes, and also extendable to explore gene cooperativity in complex diseases. The predicted genetic landscape of over 1000 human phenotypes, which reveals the global modular organization of phenotype-genotype relationships. The genome-wide prioritization of candidate genes for over 5000 human phenotypes, including those with under-characterized disease loci or even those lacking known association, is publicly released to facilitate future discovery of disease genes.

Item Type: Paper
Subjects: bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification
diseases & disorders
bioinformatics > genomics and proteomics > genetics & nucleic acid processing
bioinformatics > genomics and proteomics
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function
organism description > animal > mammal > primates > hominids > human
CSHL Authors:
Communities: CSHL labs > Zhang lab
Depositing User: Matt Covey
Date: 2008
Date Deposited: 25 Feb 2013 22:04
Last Modified: 25 Feb 2013 22:04
PMCID: PMC2424293
Related URLs:
URI: https://repository.cshl.edu/id/eprint/27579

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