Uncover disease genes by maximizing information flow in the phenome–interactome network | Zendy

Yong Chen | Zendy; Tao Jiang | Zendy; Rui Jiang | Zendy

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Uncover disease genes by maximizing information flow in the phenome–interactome network

Author(s) -

Yong Chen,

Tao Jiang,

Rui Jiang

Publication year - 2011

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btr213

Subject(s) - interactome , phenome , computational biology , candidate gene , gene , biological network , computer science , robustness (evolution) , gene regulatory network , interaction network , phenotype , biology , genetics , gene expression

Pinpointing genes that underlie human inherited diseases among candidate genes in susceptibility genetic regions is the primary step towards the understanding of pathogenesis of diseases. Although several probabilistic models have been proposed to prioritize candidate genes using phenotype similarities and protein-protein interactions, no combinatorial approaches have been proposed in the literature.

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