Detecting overlapping protein complexes in protein-protein interaction networks

Abstract

We introduce clustering with overlapping neighborhood expansion (ClusterONE), a method for detecting potentially overlapping protein complexes from protein-protein interaction data. ClusterONE-derived complexes for several yeast data sets showed better correspondence with reference complexes in the Munich Information Center for Protein Sequence (MIPS) catalog and complexes derived from the Saccharomyces Genome Database (SGD) than the results of seven popular methods. The results also showed a high extent of functional homogeneity.

Figure 1

Benchmark results. (a) Results using MIPS data sets. Shades of the same color denote individual quality scores; the total height of each bar is the value of the composite score. Numbers are the values for each score. The first four data sets are weighted, BioGRID is unweighted. Asterisks mark algorithms that could handle overlaps. AP, affinity propagation. (b) Subunits of RSC and SWI/SNF chromatin-remodeling complexes in the reference data set, as detected by ClusterONE and MCL. Shaded areas denote detected complexes.