Inferring dynamic architecture of cellular networks using time series of gene expression, protein and metabolite data | Zendy

Eduardo D. Sontag | Zendy; Anatoly Kiyatkin | Zendy; Boris Ν. Kholodenko | Zendy

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Inferring dynamic architecture of cellular networks using time series of gene expression, protein and metabolite data

Author(s) -

Eduardo D. Sontag,

Anatoly Kiyatkin,

Boris Ν. Kholodenko

Publication year - 2004

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/bth173

Subject(s) - node (physics) , computer science , computational biology , gene regulatory network , proteomics , genomics , functional genomics , systems biology , series (stratigraphy) , gene , biology , gene expression , genome , genetics , paleontology , structural engineering , engineering

High-throughput technologies have facilitated the acquisition of large genomics and proteomics datasets. However, these data provide snapshots of cellular behavior, rather than help us reveal causal relations. Here, we propose how these technologies can be utilized to infer the topology and strengths of connections among genes, proteins and metabolites by monitoring time-dependent responses of cellular networks to experimental interventions.

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