A simple method for reverse engineering causal networks

被引：8
|
作者：
Andrecut, M. [1 ]
Kauffman, S. A. [1 ]
机构：
[1] Univ Calgary, Inst Biocomplex & Informat, Calgary, AB T2N 1N4, Canada
来源：
JOURNAL OF PHYSICS A-MATHEMATICAL AND GENERAL | 2006年 / 39卷 / 46期
关键词：
D O I：
10.1088/0305-4470/39/46/L01
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
We present a simple method for 'reverse engineering' causal networks, based on mutual information, as a correlation measure. The goal of our method is not to recover all the causal interactions in a network but rather to recover some causal interactions with a very high confidence. For this purpose, we derive an 'exact' theoretical result for the statistical significance of mutual information. Also, we give some numerical simulation results, obtained for random Boolean networks, as an idealized model of genetic regulatory networks.
引用
收藏
页码：L647 / L655
页数：9
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