A Synthesis Method of Gene Regulatory Networks based on Gene Expression by Network Learning

Abstract

Investigating gene regulatory networks is important to understand mechanisms of cellular functions. Recently, the synthesis of gene regulatory networks having desired functions has become of interest to many researchers because it is a complementary approach to understanding gene regulatory networks, and it could be the first step in controlling living cells. In this chapter, we discuss a synthesis problem in gene regulatory networks by network learning. The problem is to determine parameters of a gene regulatory network such that it possesses given gene expression pattern sequences as desired properties. We also discuss a controller synthesis method of gene regulatory networks. Some experiments illustrate the performance of this method.

Key Terms in this Chapter

Network learning: method solving optimization problem

Discrete-time network: network described by difference equations

Synthesis method: method of synthesizing gene regulatory networks possessing desired behavior

Gene Regulatory Network: network describing interactions among genes

Expression pattern sequence: describe changes of expression levels of genes

Expression Pattern: describe expression levels of genes

Controller synthesis problem: synthesis problem of controller gene regulatory networks