Detecting subnetwork-level dynamic correlations | Zendy

Yan Yan | Zendy; Shangzhao Qiu | Zendy; Zhuxuan Jin | Zendy; Sihong Gong | Zendy; Yun Bai | Zendy; Jianwei Lu | Zendy; Tianwei Yu | Zendy

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Detecting subnetwork-level dynamic correlations

Author(s) -

Yan Yan,

Shangzhao Qiu,

Zhuxuan Jin,

Sihong Gong,

Yun Bai,

Jianwei Lu,

Tianwei Yu

Publication year - 2016

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/btw616

Subject(s) - subnetwork , biological network , gene regulatory network , computer science , dynamic network analysis , computational biology , network analysis , interaction network , gene , biology , genetics , gene expression , computer network , physics , computer security , quantum mechanics

The biological regulatory system is highly dynamic. The correlations between many functionally related genes change over different biological conditions. Finding dynamic relations on the existing biological network may reveal important regulatory mechanisms. Currently no method is available to detect subnetwork-level dynamic correlations systematically on the genome-scale network. Two major issues hampered the development. The first is gene expression profiling data usually do not contain time course measurements to facilitate the analysis of dynamic relations, which can be partially addressed by using certain genes as indicators of biological conditions. Secondly, it is unclear how to effectively delineate subnetworks, and define dynamic relations between them.

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