关键词: Spark, 分布式计算, 关键蛋白质检测, 介数中心性

Abstract: Spark is widely used in various fields as a distributed processing framework in big data field. For the key protein prediction in Protein-Protein Interaction（PPI） networks, the Betweenness Centrality（BC） which is based on the topology properties of PPI networks has a good prediction effect. In this paper, a new index called L1-BC is presented, which not only distinguishes some proteins with the same values of BC index, but also reflects the local properties of proteins. The experimental results show that the index L1-BC can improve the accuracy of key proteins prediction. In addition, the parallel computing algorithm of L1-BC is implemented based on Spark platform, in which the memory is greatly optimized by utilizing accumulator and broadcast variable. The results of acceleration ratio experiment on the dataset YDIP show that the optimized L1-BC algorithm on the Spark can reach the acceleration ratio of 94.31%.

Key words: Spark, distributed computing, key proteins prediction, betweenness centrality