Combining many interaction networks to predict gene function and analyze gene lists

被引：44

作者：

Mostafavi, Sara ^{[2
]}

Morris, Quaid ^{[1
,3
,4
,5
]}

机构：

[1] Univ Toronto, Banting & Best Dept Med Res, Toronto, ON M5S3E1, Canada

[2] Stanford Univ, Dept Comp Sci, Stanford, CA 94305 USA

[3] Univ Toronto, Dept Mol Genet, Toronto, ON M5S3E1, Canada

[4] Univ Toronto, Dept Comp Sci, Toronto, ON M5S3E1, Canada

[5] Univ Toronto, Donnelly Ctr, Toronto, ON M5S3E1, Canada

来源：

PROTEOMICS | 2012年 / 12卷 / 10期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Algorithm; Bioinformatics; Functional genomics; Molecular interaction; Web tool; BIOLOGICAL NETWORKS; PROTEIN COMPLEXES; HUMAN GENOME; IDENTIFICATION; INTEGRATION; LANDSCAPE; GENEMANIA; SYSTEM; MOUSE; ASSOCIATION;

D O I：

10.1002/pmic.201100607

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

In this article, we review how interaction networks can be used alone or in combination in an automated fashion to provide insight into gene and protein function. We describe the concept of a gene-recommender system that can be applied to any large collection of interaction networks to make predictions about gene or protein function based on a query list of proteins that share a function of interest. We discuss these systems in general and focus on one specific system, GeneMANIA, that has unique features and uses different algorithms from the majority of other systems.

引用

页码：1687 / 1696

页数：10

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