Finding Genetic network using Graphical Gaussian Model

Abstract

The paper proposes a simple method for constructing gene regulatory network from the microarray gene expression time series data set of `Burkholderia Pseudomalli' at various phases of growth in vitro. This has been collected from GEO data base of NCBI web-site (a genetic time series data consists of 5289 genes & 48 samples). These microarray data set represents the external manifestation of internal genetic network manipulation (as seen from central dogma). Discovering the hidden genetic network from microarray data is the prime objective of this paper. Since the number of data is huge, here first the microarray data set has been clustered into 135 clusters using k-mean clustering algorithm. This represents important information sets where each cluster is considered to contain gene set of similar expression level. The genetic network has been constructed using graphical Gaussian model i.e. GGM amongst the clusters. Thus network developed will help in detecting the culprit gene set, which will ultimately lead to `drug discovery'.