Computational Approaches for Analyzing Information Flow in Biological Networks

被引:129
作者
Kholodenko, Boris
Yaffe, Michael B. [2 ,3 ]
Kolch, Walter [1 ]
机构
[1] Univ Coll Dublin, Conway Inst Biomol & Biomed Res, Dublin 4, Ireland
[2] MIT, David H Koch Inst Integrat Canc Res, Dept Biol, Cambridge, MA 02139 USA
[3] MIT, David H Koch Inst Integrat Canc Res, Dept Biol Engn, Cambridge, MA 02139 USA
基金
爱尔兰科学基金会;
关键词
INCOHERENT FEEDFORWARD LOOP; PROTEIN-SIGNALING NETWORKS; NEGATIVE-FEEDBACK; COMBINATORIAL COMPLEXITY; FUNCTIONAL-ANALYSIS; MASS-SPECTROMETRY; RNAI SCREEN; KINASE; PATHWAYS; REVEALS;
D O I
10.1126/scisignal.2002961
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
070307 [化学生物学]; 071010 [生物化学与分子生物学];
摘要
The advancements in "omics" (proteomics, genomics, lipidomics, and metabolomics) technologies have yielded large inventories of genes, transcripts, proteins, and metabolites. The challenge is to find out how these entities work together to regulate the processes by which cells respond to external and internal signals. Mathematical and computational modeling of signaling networks has a key role in this task, and network analysis provides insights into biological systems and has applications for medicine. Here, we review experimental and theoretical progress and future challenges toward this goal. We focus on how networks are reconstructed from data, how these networks are structured to control the flow of biological information, and how the design features of the networks specify biological decisions.
引用
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页数:14
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