A parallel approach for accelerated parameter identification of Gene Regulatory Networks

Model Checking is one of the formal verication methods which can be used to infer parameters of a Gene Regulatory Network (GRN) using discrete formalism of Ren e Thomas. However, the sequen- tial approach for identication of these logical parameters is computa- tionally intensive and takes lot of processing time, depending on number of genes and range of their expression levels in a network. In this paper, we present an ecient approach for this problem, based on parallel com- puting. We partition the parameter space into subsets and assign them to processing elements on a distributed memory parallel computer. The presented approach is implemented by using OpenMPI and existing tool SMBioNet. The experimental results indicate that the approach is scal- able and achieves 7X speed-up, for a relatively small GRN, comprising of ve genes.

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