High Performance Computing for Microarrays Data Analysis

Abstract

Microarrays is a vital research area that is related to bioinformatics field. Microarrays is a profiling technique for gene expression. Researches can understand the relationship among genes by studying microarrays data. DNA microarrays is one type of microarrays, where the used biological substance is DNA sequence. DNA microarrays enable researchers to measure the expression levels of many genes simultaneously. One analysis task of DNA microarrays data is gene regulatory network inference. The main goal of the gene regulatory network inference is understanding the topological order of genes interaction and how the gene affects each other. Various gene regulatory network inference techniques have been proposed. Nevertheless, unfortunately, the gene regulatory network construction task is time-consuming and computationally intensive because of the microarrays data massive size. Therefore, parallel techniques are an absolute need for microarrays data analysis. In this research, a fully integrated framework for