Toward the dynamic interactome: it's about time

被引：182

作者：

Przytycka, Teresa M. ^{[1
]}

Singh, Mona ^{[4
,5
]}

Slonim, Donna K. ^{[2
,3
]}

机构：

[1] NIH, Natl Ctr Biotechnol Informat, Natl Lib Med, Res Grp Algorithms & Graph Theory Computat & Syst, Bethesda, MD 20814 USA

[2] Tufts Univ, Dept Comp Sci, Medford, MA 02155 USA

[3] Tufts Univ, Dept Pathol, Sch Med, Medford, MA 02155 USA

[4] Princeton Univ, Dept Comp Sci, Princeton, NJ 08544 USA

[5] Princeton Univ, Lewis Sigler Inst Integrat Genom, Princeton, NJ 08544 USA

来源：

BRIEFINGS IN BIOINFORMATICS | 2010年 / 11卷 / 01期

基金：

美国国家卫生研究院; 美国国家科学基金会;

关键词：

network analysis; network dynamics; interaction networks; systems biology; PROTEIN-INTERACTION MAP; TRANSCRIPTIONAL REGULATORY NETWORK; INTEGRATIVE GENOMICS APPROACH; GENE-EXPRESSION; SACCHAROMYCES-CEREVISIAE; SIGNALING PATHWAYS; HIERARCHICAL STRUCTURE; MODULAR ARCHITECTURE; YEAST; COMPLEXES;

D O I：

10.1093/bib/bbp057

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Dynamic molecular interactions play a central role in regulating the functioning of cells and organisms. The availability of experimentally determined large-scale cellular networks, along with other high-throughput experimental data sets that provide snapshots of biological systems at different times and conditions, is increasingly helpful in elucidating interaction dynamics. Here we review the beginnings of a new subfield within computational biology, one focused on the global inference and analysis of the dynamic interactome. This burgeoning research area, which entails a shift from static to dynamic network analysis, promises to be a major step forward in our ability to model and reason about cellular function and behavior.

引用

页码：15 / 29

页数：15

共 181 条

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