COSINE: COndition-SpecIfic sub-NEtwork identification using a global optimization method | Zendy

Haisu Ma | Zendy; Eric E. Schadt | Zendy; Lee M. Kaplan | Zendy; Hongyu Zhao | Zendy

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COSINE: COndition-SpecIfic sub-NEtwork identification using a global optimization method

Author(s) -

Haisu Ma,

Eric E. Schadt,

Lee M. Kaplan,

Hongyu Zhao

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/btr136

Subject(s) - computer science , identification (biology) , cosine similarity , relevance (law) , data mining , expression (computer science) , population , r package , selection (genetic algorithm) , computational biology , pattern recognition (psychology) , artificial intelligence , biology , botany , demography , computational science , sociology , political science , law , programming language

The identification of condition specific sub-networks from gene expression profiles has important biological applications, ranging from the selection of disease-related biomarkers to the discovery of pathway alterations across different phenotypes. Although many methods exist for extracting these sub-networks, very few existing approaches simultaneously consider both the differential expression of individual genes and the differential correlation of gene pairs, losing potentially valuable information in the data.

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