关键词: 功能模块检测, 蛋白质相互作用网络, 花授粉算法, 异花授粉, 自花授粉

Abstract: Revealing unknown functions of proteins were one of the core contents of proteomics in the post gene era, where it had become a hotspot to use the swarm intelligence-based approaches to identify functional modules in protein-protein interaction networks(PPIN). An approach based on flower pollination algorithm to detect functional modules in PPIN was proposed. Each pollen in the population was encoded by a random walk and the population was optimized by using two mechanisms of self-pollination and cross-pollination which were specially owned by flower pollination algorithm. More specially, the strategies of recombination and better-solution selection were adopted in the self-pollination while the mutation strategies based on Levy mechanism and an adaptive individual-difference were employed in the cross-pollination. The four strategies together promoted the evolution of the population from different angles. The simulation experiments on three public data sets showed that the proposed algorithm had not only excellent overall performance but also absolute superiority in terms of two comprehensive indicators F-measure and accuracy compared with the other six classical algorithms.

Key words: self-pollination, functional module detection, flower pollination algorithm, cross-pollination, protein-protein interaction network