Integrating protein-protein interaction networks with phenotypes reveals signs of interactions

被引：0
|
作者：
Vinayagam A. [1 ]
Zirin J. [1 ]
Roesel C. [1 ,2 ,3 ,5 ]
Hu Y. [1 ,2 ]
Yilmazel B. [1 ,2 ,3 ]
Samsonova A.A. [1 ]
Neumüller R.A. [1 ]
Mohr S.E. [1 ,2 ]
Perrimon N. [1 ,4 ]
机构：
[1] Department of Genetics, Harvard Medical School, Boston, MA
[2] Drosophila RNAi Screening Center, Department of Genetics, Harvard Medical School, Boston, MA
[3] Bioinformatics Program, Northeastern University, Boston, MA
[4] Howard Hughes Medical Institute, Boston, MA
[5] Marine Science Center, Northeastern University, Nahant, MA
来源：
Nature Methods | 2014年 / 11卷 / 1期
关键词：
D O I：
10.1038/nmeth.2733
中图分类号：
学科分类号：
摘要：
A major objective of systems biology is to organize molecular interactions as networks and to characterize information flow within networks. We describe a computational framework to integrate protein-protein interaction (PPI) networks and genetic screens to predict the 'signs' of interactions (i.e., activation-inhibition relationships). We constructed a Drosophila melanogaster signed PPI network consisting of 6,125 signed PPIs connecting 3,352 proteins that can be used to identify positive and negative regulators of signaling pathways and protein complexes. We identified an unexpected role for the metabolic enzymes enolase and aldo-keto reductase as positive and negative regulators of proteolysis, respectively. Characterization of the activation-inhibition relationships between physically interacting proteins within signaling pathways will affect our understanding of many biological functions, including signal transduction and mechanisms of disease.
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页码：94 / 99
页数：5
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