Identification And Analysis Of Disease Genes Based On Biological Network

The study found that genes are closely related to the production of disease,and the mutation and abnormality of the gene are often important factors that cause the disease.In order to further understand the mechanism of disease,develop new drugs and improve the level of medical treatment,the use of bioinformatics to mine disease related genes has gradually become the focus of researchers in the field of contemporary biology.Based on complex network theory,we analyzed colorectal related gene expression data,identified important genes related to colorectal cancer,and validated the identified genes,and explored the role of these genes in the development of colorectal cancer.The specific work is as follows:(1)GSE9348 gene expression data and 135 colorectal cancer genes were down-loaded from GEO database and OMIM database respectively.The GSE9348 gene expression data was reduced and screened by R package,and 339 differentially expressed genes were obtained.Screening 339 differentially expressed genes and 135 colorectal cancer known disease genes to the STRING database,get the differentially expressed genes with known disease genes of protein interaction networks,and further through the Cytoscape software for visualization.After that,according to the cluded plug-in of the Cytoscape software,a module analysis was carried out on the obtained protein interaction network,and a sub-network containing 53 genes was obtained.Finally,five new colorectal cancer genes were identified by analyzing the topological properties of subnetworks.At the same time,the newly discovered pathogenic genes were verified by functional enrichment analysis and literature mining.(2)On the basis of gene expression data,using t test analysis of these five recognition pathogenic gene expression in colorectal cancer,the gene significantly high expression in colorectal cancer was obtained.Then,based on the clinical data of colorectal cancer,the relationship between the expression of these pathogenic genes and the clinical phenotype was analyzed,and the patients with high expression group and low expression group was significant difference in clinical phenotype.Finally,through survival analysis and Spearman correlation analysis,it is proved that these pathogenic genes have an important influence on the prognosis of colorectal cancer,and can be an independent prognostic factor.The prediction of genes related to disease by biological network can effectively predict genetic diseases and other related genes,and provide valuable reference information for the research of genetics and other related disciplines.