Linear Control Theory for Gene Network Modeling

被引：12

作者：

Shin, Yong-Jun ^{[1
]}

Bleris, Leonidas ^{[1
,2
]}

机构：

[1] Univ Texas Dallas, Dept Elect Engn, Richardson, TX 75083 USA

[2] Univ Texas Dallas, Dept Bioengn, Richardson, TX 75083 USA

来源：

PLOS ONE | 2010年 / 5卷 / 09期

关键词：

REGULATORY NETWORKS; SYNTHETIC BIOLOGY; EXPRESSION; CIRCUIT; NOISE; SYSTEMS; ROBUST; MOTIFS;

D O I：

10.1371/journal.pone.0012785

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain) and linear state-space (time domain) can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.

引用

页码：1 / 16

页数：16

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