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应用于蛋白质折叠问题的混沌多猝灭退火

Chaotic multiquenching annealing applied to the protein folding problem.

作者信息

Frausto-Solis Juan, Liñan-García Ernesto, Sánchez-Pérez Mishael, Sánchez-Hernández Juan Paulo

机构信息

Universidad Politécnica del Estado de Morelos Boulevard, Cuauhnáhuac 566, 62660 Jiutepec, Mexico.

Universidad Autónoma de Coahuila Boulevard, Venustiano Carranza s/n, 25280 Saltillo, Mexico.

出版信息

ScientificWorldJournal. 2014 Mar 20;2014:364352. doi: 10.1155/2014/364352. eCollection 2014.

Abstract

The Chaotic Multiquenching Annealing algorithm (CMQA) is proposed. CMQA is a new algorithm, which is applied to protein folding problem (PFP). This algorithm is divided into three phases: (i) multiquenching phase (MQP), (ii) annealing phase (AP), and (iii) dynamical equilibrium phase (DEP). MQP enforces several stages of quick quenching processes that include chaotic functions. The chaotic functions can increase the exploration potential of solutions space of PFP. AP phase implements a simulated annealing algorithm (SA) with an exponential cooling function. MQP and AP are delimited by different ranges of temperatures; MQP is applied for a range of temperatures which goes from extremely high values to very high values; AP searches for solutions in a range of temperatures from high values to extremely low values. DEP phase finds the equilibrium in a dynamic way by applying least squares method. CMQA is tested with several instances of PFP.

摘要

提出了混沌多重淬火退火算法(CMQA)。CMQA是一种新算法,应用于蛋白质折叠问题(PFP)。该算法分为三个阶段:(i)多重淬火阶段(MQP),(ii)退火阶段(AP),以及(iii)动态平衡阶段(DEP)。MQP执行包括混沌函数的多个快速淬火过程阶段。混沌函数可以增加PFP解空间的探索潜力。AP阶段采用具有指数冷却函数的模拟退火算法(SA)。MQP和AP由不同的温度范围界定;MQP应用于从极高值到非常高值的温度范围;AP在从高值到极低值的温度范围内搜索解。DEP阶段通过应用最小二乘法以动态方式找到平衡。用PFP的几个实例对CMQA进行了测试。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbcc/3980881/12aeeab7a861/TSWJ2014-364352.001.jpg

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