A genetic algorithm with backtracking for protein structure prediction

被引：0

作者：

Johnson, Clayton Matthew ^{[1
]}

Katikireddy, Anitha ^{[1
]}

机构：

[1] Calif State Univ East Bay, Dept Math & Comp Sci, Hayward, CA 94542 USA

来源：

GECCO 2006: GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, VOL 1 AND 2 | 2006年

关键词：

genetic algorithms; HP model; protein structure prediction;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we propose a simple genetic algorithm for finding the optimal conformation of a protein using the three-dimensional square HP model. A backtracking procedure is used to resolve the positional collisions and illegal conformations that occur during the course of genetic search. Backtracking is shown to be a simple and efficient means of collision repair that requires little overhead. Empirical results show that a genetic algorithm using backtracking can obtain the lowest energy structure of an amino acid sequence in fewer energy evaluations than earlier approaches.

引用

页码：299 / +

页数：2