Discover Protein Complexes in Protein-Protein Interaction Networks Using Parametric Local Modularity

Discover Protein Complexes in Protein-Protein Interaction Networks Using Parametric Local Modularity

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Abstract Background Recent advances in proteomic technologies have enabled us to create detailed protein-protein interaction maps in multiple species and in both normal and diseased cells.As the size of the interaction dataset increases, powerful computational methods are required in order to effectively distil network models from large-scale interactome data.Results We present an algorithm, miPALM (Module Inference by Parametric Local Modularity), to Nails infer protein complexes in a protein-protein interaction network.The algorithm uses a novel graph theoretic measure, parametric local modularity, to identify highly connected sub-networks as candidate protein complexes.

Using gold standard sets of protein complexes and protein function Cushion and localization annotations, we show our algorithm achieved an overall improvement over previous algorithms in terms of precision, recall, and biological relevance of the predicted complexes.We applied our algorithm to predict and characterize a set of 138 novel protein complexes in S.cerevisiae.Conclusions miPALM is a novel algorithm for detecting protein complexes from large protein-protein interaction networks with improved accuracy than previous methods.

The software is implemented in Matlab and is freely available at http://www.medicine.uiowa.edu/Labs/tan/software.

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