Predicting dynamic signaling network response under unseen perturbations | Zendy

Fan Zhu | Zendy; Yuanfang Guan | Zendy

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Predicting dynamic signaling network response under unseen perturbations

Author(s) -

Fan Zhu,

Yuanfang Guan

Publication year - 2014

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/btu382

Subject(s) - computer science , regularization (linguistics) , code (set theory) , source code , machine learning , systems biology , artificial intelligence , algorithm , bioinformatics , set (abstract data type) , biology , programming language , operating system

Predicting trajectories of signaling networks under complex perturbations is one of the most valuable, but challenging, tasks in systems biology. Signaling networks are involved in most of the biological pathways, and modeling their dynamics has wide applications including drug design and treatment outcome prediction.

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