A MPI Based Parallel Algorithm for Inferring Gene Regulatory Networks

Gene regulatory network (GRN) is an important tool in post genomic era, and its construction algorithms are concerned by many researchers. However, Most of the algorithms have high computation complexity and cannot be easily solved in a satisfied time. So how to design a structure to accelerate the algorithms is a problem to researchers. This paper is to develop a parallel algorithm that adopts Message Passing Interface (MPI) parallel technology for gene regulatory network inferring based on time-delayed mass action model to accelerate computation. Experiments on three well-known motifs and a real biological data set of GRN show that the proposal can make full use of the existing multi-core computers' computation resources and improved the computation efficiency of the network construction.