| The identifying of disease-causing genes and the study of disease-causing mechanisms are of great significance for disease treatment and prevention.In order to mine the related genes of autism,this paper first designed a systematic data screening algorithm for the difference between the experimental group and the control group using statistical hypothesis testing,and implemented the algorithm using MATLAB software.Then the algorithm was applied to the gene expression profile data of autism(GSE25507).244 genes with a large difference in expression profile between the experimental group and the control group were selected as genes related to autism from the 23520 gene.This has greatly narrowed the scope of research for further predicting the genes responsible for autism.Through gene annotation,the genes known in the literature related to autism,such as FIGF,MED 13,NDRG4,POU3F2 and USP8,were found in the 244 genes screened,which shows the effectiveness of the algorithm.Finally,the structural parameters(average degree)of the gene's correlation network are used to mine the structural key genes of autism and study the pathogenic mechanism.Based on the 244 genetic data screened by the data,we established the Spearman correlation network of the experimental group and the control group,analyzed the average of the network under different thresholds,and found that the average degree of the experimental group and the control group was basically separable at the full threshold.This shows that there is a clear difference between the genetic network structure of the control group and the experimental group,and it also suggests that this difference is related to the mechanism of the disease.Through literature annotation and enrichment analysis of the top 20 genes(structural key genes)with large differences in average degree,they were found to be related to the development of the glands of the nervous system,cardiovascular development and morphogenesis of embryonic organs.This supports the conclusion that the overall level of gene expression regulation may affect systems other than the brain,as well as developmental disorders of the nervous system and symptoms that may trigger autism.The structural key genes FIGF and CSF3 are likely to play an important role in the mechanism of autism.In order to identify the causative genes of acute myocardial infarction and study the pathogenic mechanism of acute myocardial infarction,we first selected 292 genes related to acute myocardial infarction using data screening algorithm,and then constructed gene expression profiles of patients with acute myocardial infarction and healthy people The correlation network of the network,the clustering coefficient curve under different thresholds of the network can select genes with large differences in clustering coefficients,and perform GO and KEGG enrichment analysis to find that they are significantly related to the immune system,especially inflammation Processes and Nod-like receptor signaling pathways.This is not only consistent with the existing literature,but the literature has confirmed that 17 of the structural key genes are significantly associated with acute cardiac infarction.According to literature notes,the OAS-RNASEL metabolic pathway and miR-92a-3p may play a key role in the mechanism of acute myocardial infarction.In addition,MAFF,EOMES,IL22,BST1,TMEM63A,GIMAP1,GIMAP4,and GIMAP6 may be diagnostic markers for acute myocardial infarction.Despite the lack of experimental verification,this study still has the significance of further research,provides potential new key genes for further experimental verification,and reveals the pathogenic mechanism of acute myocardial infarction... |
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