Dataset Information
Identifying functional modules in interaction networks through overlapping Markov clustering.
Ontology highlight
ABSTRACT: Motivation
In recent years, Markov clustering (MCL) has emerged as an effective algorithm for clustering biological networks-for instance clustering protein-protein interaction (PPI) networks to identify functional modules. However, a limitation of MCL and its variants (e.g. regularized MCL) is that it only supports hard clustering often leading to an impedance mismatch given that there is often a significant overlap of proteins across functional modules.Results
In this article, we seek to redress this limitation. We propose a soft variation of Regularized MCL (R-MCL) based on the idea of iteratively (re-)executing R-MCL while ensuring that multiple executions do not always converge to the same clustering result thus allowing for highly overlapped clusters. The resulting algorithm, denoted soft regularized Markov clustering, is shown to outperform a range of extant state-of-the-art approaches in terms of accuracy of identifying functional modules on three real PPI networks.Availability
All data and codes are freely available upon request.Contact
srini@cse.ohio-state.eduSupplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Shih YK
PROVIDER: S-EPMC3436797 | biostudies-literature | 2012 Sep
REPOSITORIES: biostudies-literature
Publications
Identifying functional modules in interaction networks through overlapping Markov clustering.
Bioinformatics (Oxford, England) 20120901 18
<h4>Motivation</h4>In recent years, Markov clustering (MCL) has emerged as an effective algorithm for clustering biological networks-for instance clustering protein-protein interaction (PPI) networks to identify functional modules. However, a limitation of MCL and its variants (e.g. regularized MCL) is that it only supports hard clustering often leading to an impedance mismatch given that there is often a significant overlap of proteins across functional modules.<h4>Results</h4>In this article, ...[more]