Construction Of Gene Effect And Signaling Mathematical Models With Application

The polygenic function is greatly noticed by genetic academics for a long time, For the developing of multiple discipline, To date, there are only two main analysis method to solve the questions. One is QTL (quantitative trait locus) analysis method and the other is the bioinformatics method. Now, many QTL (quantitative trait locus) analysis methods, which include mean-variance approach, moment and mikelihood approach and regression approach et al, have been proposed to estimate the effect of main genes controlling the quantitative trait. However, we can find that sometimes we got ghost QTL after estimation, and there after the QTL parameter estimated are not precise. Furthermore, according to systemic theory, there exist many points need to be developed in the estimation approach of QTL parameters. On the other hand, graphic theory approach has been prospected for the signaling represantation by many scholars for analyzing molecular networks, and has been combined with automatic analysis by computers. However, graphic theory approach has not been used in the research of molecular network analysis, or only primarily, but intricately. In this article, to estimation approach of gene effect, we establish genetic model and develop an approach to estimate the polygenic effect and gene types, the validity of this approach is proved by mathematical induction and computer simulation. To research the interaction between molecules, we established a graphic model and develop a simple program to analyze the signal transduction, the validity of this procedure is proved by molecular biological technique, and as an example, the FOXO signaling is elucidated by the graphic programming as well as molecular biological technique.The approach to estimate the gene effect and type:Firstly, collecting data: Collect the data of gene expression and quantitative trait with their corresponding molecular marker states by experimental method or measurement.Secondly, quantifying markers: Because gene's polymorphism or the codominant molecular marker electropherogram in a gene locus present 3 states, we can quantify them with -1,0 and 1 respectively.