Construction Of Differential Expression Gene Analysis System Based On GEO Database

The completion of human genome project and the rapid development of bioinformatics and other disciplines,genomics gradually from gene sequencing study reveals the essence of life genetic information is transferred to the study of gene function from the molecular level.Bioinformatics has also been transferred from the original genome sequence to the biological significance of gene expression profile data.The rapid development of bioinformatics and related disciplines has led to a large number of biological data showing exponential growth patterns.Founded by NCBI Gene Expression database（Gene Expression Omnibus,GEO）,a strong collection and storage capabilities,covering multiple high-throughput experimental data in the field of biology and bioinformatics researchers provide a lot of disease related Gene Expression spectrum information.How to effectively use these biological data,excavate the potential biological value,used in gene analysis,gene expression and regulation,the diagnosis of disease,drug screening,has become a functional genomics era under one of the important task in bioinformatics research.Gene chip,as a tool for obtaining biological information data in batches,provides a large number of gene expression profiles.Through deep excavation and analysis of these data,it is helpful to understand the function of genes and the interaction between genes.In order to achieve this goal,the key link is to detect and analyze the difference expression genes of pathological tissues and normal tissues from the large gene expression profile information^[1].In functional genomics era,in order to promote the research and development of bioinformatics and other disciplines,using gene chip technology to build good GEO database analysis system of the differentially expressed genes is more important.At present,the technology of the differentially expressed genes in the analysis are:differential display PCR technology,cut hybrid technology,typical gap analysis technology,curb cuts hybrid technology,etc.,require complex screening experiment,time-consuming and laborious.In this paper,we study the differentially expressed genes of analysis system is based on the GEO database of gene expression profile information data using the Python code is compiled for all disease gene expression spectrum information automatically,and standardizing,combined with statistical T test model calculation value differences in gene expression,and then screen out there are differences between the expression of genes,and to provide support for follow-up study.Its greatest feature is the analysis of gene expression from the differential expression of a single disease to an automatic,rapid,and accurate screening of the differentially expressed genes of all diseases from a systematic perspective.At the moment,the screening of differentially expressed genes work is relatively complex and time-consuming,differentially expressed genes analysis researchers are mostly limited to the microarray expression data analysis of the single disease.Differentially expressed genes based on the research analysis system can detect the disease related genes differentially expressed screening,for the majority of bioinformatics researchers provide accurate screening results,simplify the analysis process,improve the utilization rate of resources.Also help to push the differentially expressed genes analysis technology and screening results of practical application,the analysis of differentially expressed genes can help more researchers at the genome level to reveal the pathogenesis of the disease looking for new targeted therapeutic targets,to find and identify leads to new sequence variation of drug resistance,will not only help to find the pathogenesis of the disease from genome level for targeted treatment resistant mechanism of disease research.