Abstract
The detection of complexes in protein–protein interaction (PPI) network bears great significance in predicting unknown protein and providing theoretical basis for various researches on a wide array of diseases. In this paper, a PPI network complexes detection algorithm based on Harmony Search Clustering Optimization Model (HMS-CD) is being proposed. Compared with the traditional harmony search algorithm, dynamic parameter of HMCR and BW is introduced to improve the search strategy. The method to find a set of nodes with a larger aggregation coefficient in PPI network is regarded as the objective function of the proposed algorithm. The experimental result on a real dataset like yeast PPI network shows that the proposed algorithm achieves better detection accuracy than traditional harmony search (HMS) algorithm and typical MCODE algorithm, and it can detect complexes in PPI network more effectively.
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