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.

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Figure 1: Benchmark results.

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Acknowledgements

T.N. was supported by the Newton International Fellowship Scheme of the Royal Society grant NF080750. A.P. was supported by the Biotechnology and Biological Sciences Research Council New Investigator grant BB/F00964X/1. H.Y. was supported by US National Institute of General Medical Sciences grant R01 GM097358.

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Authors

Contributions

T.N. and A.P. conceived the study. T.N. devised and implemented the algorithm and conducted benchmarks. H.Y. evaluated the biological relevance of the results. A.P. supervised the project. H.Y., T.N. and A.P. discussed the results and implications. A.P. and T.N. wrote the manuscript.

Corresponding authors

Correspondence to Haiyuan Yu or Alberto Paccanaro.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–8, Supplementary Tables 1–4, Supplementary Discussion (PDF 1310 kb)

Supplementary Data 1

Input data files used in the benchmarks. (ZIP 525 kb)

Supplementary Data 2

Gold standard data files used in the benchmarks. (ZIP 17 kb)

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Nepusz, T., Yu, H. & Paccanaro, A. Detecting overlapping protein complexes in protein-protein interaction networks. Nat Methods 9, 471–472 (2012). https://doi.org/10.1038/nmeth.1938

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