Reverse engineering of temporal Boolean networks from noisy data using evolutionary algorithms

被引：4

作者：

Cotta, C ^{[1
]}

Troya, JM ^{[1
]}

机构：

[1] Univ Malaga, ETSI Informat, Dept Lenguajes & Ciencias Computac ETSI Informat, E-29071 Malaga, Spain

来源：

NEUROCOMPUTING | 2004年 / 62卷

关键词：

biocomputation; genetic network inference; Temporal Boolean Networks; evolutionary algorithms; noisy data;

D O I：

10.1016/j.neucom.2003.12.007

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We consider the problem of inferring a genetic network from noisy data. This is done under the Temporal Boolean Network Model. Owing to the hardness of the problem, we propose an heuristic approach based on the combined utilization of evolutionary algorithms and other existing algorithms. The main features of this approach are the, heuristic seeding of the initial population, the utilization of a specialized recombination operator, and the use of a majority-voting procedure in order to build a consensus solution. Experimental results provide support for the potential usefulness of this approach. (C) 2003 Elsevier B.V. All rights reserved.

引用

页码：111 / 129

页数：19

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