Identifying functional modules in interaction networks through overlapping Markov clustering.

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 al

SUBMITTER: Shih YK 

PROVIDER: S-EPMC3436797 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature