Attractors in Boolean networks: a tutorial

被引：34
|
作者：
Hopfensitz, Martin [1 ]
Muessel, Christoph [1 ]
Maucher, Markus [1 ]
Kestler, Hans A. [1 ]
机构：
[1] Univ Ulm, Res Grp Bioinformat & Syst Biol, Inst Neural Informat Proc, D-89069 Ulm, Germany
来源：
COMPUTATIONAL STATISTICS | 2013年 / 28卷 / 01期
关键词：
Systems biology; Boolean networks; Attractors; REGULATORY NETWORKS; GENETIC NETWORKS; MODEL;
D O I：
10.1007/s00180-012-0324-2
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
Boolean networks are a popular class of models for the description of gene-regulatory networks. They model genes as simple binary variables, being either expressed or not expressed. Simulations of Boolean networks can give insights into the dynamics of cellular systems. In particular, stable states and cycles in the networks are thought to correspond to phenotypes. This paper presents approaches to identify attractors in synchronous, asynchronous and probabilistic Boolean networks and gives examples of their usage in the BoolNet R package.
引用
收藏
页码：19 / 36
页数：18
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