JI Junzhong, YANG Minghao, YANG Cuicui, HAN Yue. Fast Ant Colony Clustering for Functional Module Detection Algorithm in PPI Networks[J]. Journal of Beijing University of Technology, 2016, 42(8): 1182-1192. DOI: 10.11936/bjutxb2016010027
    Citation: JI Junzhong, YANG Minghao, YANG Cuicui, HAN Yue. Fast Ant Colony Clustering for Functional Module Detection Algorithm in PPI Networks[J]. Journal of Beijing University of Technology, 2016, 42(8): 1182-1192. DOI: 10.11936/bjutxb2016010027

    Fast Ant Colony Clustering for Functional Module Detection Algorithm in PPI Networks

    • The time performance of ant colony clustering seriously restricts its application for functional module. A fast ant colony clustering for functional module detection (FACC-FMD) algorithm, which considerably speeded up the original ACC-FMD algorithm was developed. The similarity between each protein and core protein group was computed by the FACC-FMD, then clustered by the pick-up and drop-down model. The similarity between the functional modules by clustering was small. Thus FACC-FMD eliminated the need for the merge operation and filter operation in ant colony cluster, and shorten the running time. At the same time, the essential of protein was computed and was used to constraint the times of pick-up and drop-down. Experiments on multiple PPI networks show that the FACC-FMD algorithm can greatly improve the time performance of ant colony clustering for functional module detection with satisfactory quality. Moreover, compared with classical algorithms in recent years, the FACC-FMD also has advantages in performance indicators.
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