Studying the effect of Mouse models for Gene Expression using Coregionalization Models in Gaussian process

Abstract

Gene expression of time series analysis uses and supports in many biological studies. The difference in transcriptional regulation between two strains of mice. the phenotype of the two mutant strains differ, where one of the strains succumbs to ALS far quicker than the other. The aim of the work determines a candidate list of genes or pathway that would give insight into the mechanism behind this difference of phenotype. Gaussian processes are efficient and usability for the analysis these series, Gaussian process (GP) regression with Coregionalization model have built to determine a candidate list of genes or pathway that would give insight into the mechanism behind this difference of phenotype. A model has built on these series to account for more structure within the time series; these Data have a correlated output for mouse model for ALS disease. The results of this model are well done to detect gene expression differences associated with the difference in the phenotype for four cases the genes alter its behavior and the new information that discovery genes have same behavior in both two mutations and two strains.