期刊
BIOINFORMATICS
卷 28, 期 1, 页码 84-90出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btr621
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类别
资金
- CNRS (PEPS from the STII department of the CNRS)
- ANR [09-PIRI-0028-1]
- EU ERA-NET Plus scheme [09-SYSB-0008-01]
- AXA
Motivation: Multifunctional proteins perform several functions. They are expected to interact specifically with distinct sets of partners, simultaneously or not, depending on the function performed. Current graph clustering methods usually allow a protein to belong to only one cluster, therefore impeding a realistic assignment of multifunctional proteins to clusters Results: Here, we present Overlapping Cluster Generator (OCG), a novel clustering method which decomposes a network into overlapping clusters and which is, therefore, capable of correct assignment of multifunctional proteins. The principle of OCG is to cover the graph with initial overlapping classes that are iteratively fused into a hierarchy according to an extension of Newman's modularity function. By applying OCG to a human protein-protein interaction network, we show that multifunctional proteins are revealed at the intersection of clusters and demonstrate that the method outperforms other existing methods on simulated graphs and PPI networks.
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