Reconstruction of Gene Regulatory Network using Bayesian Network

Abstract

Gene Regulatory Networks (GRN) are complicated govern systems, that refers to the intercommunication of genes and it also helps to understand and visualize all the biological interconnections. Reconstruction of GRN helps in finding out various hidden facts that can be helpful in solving various complexities related to living life, curing many diseases and inventing new drugs for the humans. There are number of computational methods available in literature for reconstructing GRNs. In this paper, a method is proposed for reconstructing GRN i.e. based upon Bayesian network. The mentioned method in this paper is considered as one of the most capable method for reconstructing GRN. The proposed method functions in two stages. In its first stage, there is two level clustering is employed to diminish the size of given dataset. In its second stage, Bayesian Network will be utilized to reconstruct the network for the sub-clusters that are gained from the first stage. The proposed method is also validated and evaluated using different parameters.