Construction And Correlation Analysis Of Genotype Interaction Network Of Human Retinal Pigment Denaturation Based On Complex Network

The analysis of pathogenesis of genetic diseases often requires large and expensive biological experiments or long-time experience accumulation of the clinical diagnosis of genetic disease. The biological data was very huge and complex. Therefore, this paper use data mining technology and complex network theory to design the discovery method of pathogenesis of genetic diseases, which makes the discovery process automation, shortens the discovery time, reduces expenses and have some reference value to predict and diagnose the illness in the molecular level.Therefore, based on human retinitis pigmentosa cases and control data set, this paper use data mining technology and complex network theory to find the pathogenic mechanism of human retinitis pigmentosa. The main researches and works of this paper are as follow:(1) high-efficiency mining algorithm for association rules between phenotypes and locus. This paper proposed match to find a biology statistical significance association rules with low support and used parallel computing to speed up association rules algorithm.(2) To construct the interaction network between loci genotypes. This paper use association rule algorithms to find the interaction between loci genotypes. This paper construct loci genotypes interaction network with loci genotypes as nodes and interaction of loci genotypes as edges. Network of cases and controls were constructed, and then this paper compare and analyze the statistical discrepancy for the proportion and topological properties of nodes between the two networks.(3) To reveal pathogenic mechanism of human retinitis pigmentosa based on Loci genotypes interaction network.This paper find 3-node motifs in cases and controls locus interaction network respectively, and then find the pathogenic mechanism of human retinitis pigmentosa by the analysis of differential network.