Clustering PPI Data Based on Bacteria Foraging Optimization Algorithm

This paper proposed a novel method using Bacteria Foraging Optimization(BFO) algorithm to avoid the influence of cluster number on experimental result of clustering PPI networks. The initial position that the bacterium located in was considered to be the cluster center and the positions that the bacterium moved were regarded as the adjacent nodes of cluster center. The algorithm classified the nodes selected in the chemotactic operation into cluster when executing the reproduction and elimination-dispersal operations. The procedure kept on creating new clusters until all the nodes were grouped into the clusters. The simulation result showed that the algorithm not only effectively improved the accuracy of cluster result, but also automatically determined the cluster number.