CommWalker: correctly evaluating modules in molecular networks in light of annotation bias.

ABSTRACT: Motivation:Detecting novel functional modules in molecular networks is an important step in biological research. In the absence of gold standard functional modules, functional annotations are often used to verify whether detected modules/communities have biological meaning. However, as we show, the uneven distribution of functional annotations means that such evaluation methods favor communities of well-studied proteins. Results:We propose a novel framework for the evaluation of communities as functional modules. Our proposed framework, CommWalker, takes communities as inputs and evaluates them in their local network environment by performing short random walks. We test CommWalker's ability to overcome annotation bias using input communities from four community detection methods on two pro

SUBMITTER: Luecken MD 

PROVIDER: S-EPMC5860269 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature