http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Controller Design Method of Gene Networks Based on Gene Expression Patterns by Network Learning
Yoshihiro Mori,Yasuaki Kuroe 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
Investigating gene networks is important for understanding mechanism of cellular functions. Recently there have been increasing research interests in synthesizing gene networks and several studies have been done. Synthesizing gene networks is a complementary approach to understanding functions of gene networks, and it could be the first step in controlling and monitoring living cells. In this paper, we discuss the controller design problem: for a given objective gene network and a desired expression pattern sequence, design a controller gene network such that the objective gene network has desired one. We propose a controller design method by discrete-time network learning in which the cost function includes evaluations of behavior of controllers. Numerical experiments are given to evaluate the performance of the proposed method.
Yoshihiro Mori,Yasuaki Kuroe 제어로봇시스템학회 2012 제어로봇시스템학회 국제학술대회 논문집 Vol.2012 No.10
There exist periodic phenomena in cells and the phenomena are considered to be generated by gene regulatory networks. Therefore synthesis of gene regulatory networks having desired periodic behavior has become of interest to many researchers. In this paper, we discuss a synthesis problem of gene regulatory networks having desired periodic behavior. The desired behavior are given by cyclic expression pattern sequences. We proposed a synthesis method for realizing a periodic solution trajectory exhibiting a desired cyclic expression pattern sequence by using Poincar`e map. In the method, we choose a point and make it become a fixed point of a Poincar´e map. However it is not always possible to make the chosen point become a fixed point. In this paper we propose a synthesis method without choosing a fixed point. We evaluate the method by performing numerical experiments.