Research On Entropy's Application In Construction Of Gene Regulatory Network

MotivationAs a powerful biological technology, gene chip has been widely used in various field of life science including gene diagnosis and gene expression. More important is that this technology plays an important role in the finding of new genes and the interaction between genes and other biomacromolecules. This is not only enhanced the development of life science but also accelerated steps to unveil the internal nature life and even the essence of life. That's why we said that gene chip has a widespread perspective. As we know, that the expression of a gene could be affected by other genes. The complex relationships formed the so-called gene regulatory networks for genes. Therefore, to reveal the details of the cellular process, trying to find out the interaction among genes is the best way. Gene chip could analyze gene expression based on the genomic level, so we could the interaction among genes using the mathematical model. However, most of the models that has existed could not analyze the regulatory from time,or hypothesis the weight of the expression of genes were totally the same at any time.Based on gene expression data, we make the seven time spots weight,and establish the gene regulatory networks of cerebel based on the correlation coefficients of information entropy.MethodBased on GO database ,we selected 60 genes which expressed at all seven time spots and were related with the development of cerebel. First,we standardize gene expression data,then, we make the data of seven time spots weight,and establish the gene regulatory networks with correlation coefficients of information entropy matrix.ResultUtilizing mutual information correlation model,correlation coefficients of infor- mation entropy matrix were gained,and matrix was established,consequently,regulatory networks relation between the genes was finded and the relation could be visualized by Matlab.ConclusionFrom the correlation coefficients of information entropy, we could describe the regulation relationships between genes. This counting method could be operated easily and the result is reasonable. It could be a new way for establishing the gene regulatory networks,and be of the foundation for farther biological experiment.