The Estimation Of Regulation Rates For FFL Based On Gibbs Sampling And Simulation Filter

An important task of postgenomic age is to study the interactions among gene, mRNA, protein and metabolic produces. Transcription regulation networks control the expression of genes and describe the interactions between transcription factors and the genes they regulate. It is found that this kind of networks are made up of the basic blocks—network motifs. Then the studys turn to the network motifs. The ability of regulation factor can be thought of a kind of stochastic reaction rates. If the rates of regulation networks can be estimated, it will play important roles in fields such as gene high performance expression, biological pharmacy, etc.In this article, the feedforward loop is interested in. Firstly, the regulation relationships of motif elements are given and the stochastic differential equation of this system can be obtained based on the diffusion approximation. Secondly, the estimation of parameters is given with the Gibbs sampling and the simulation filter. The later can overcome the fault of Gibbs sampling with slow convergence. Finally, a matlab program with simulation data gives the estimation and 95% confidence interval of parameters. The results show that applying this method on estimating the regulation rates of FFL is feasible.