基于Boltzmann和玻色-爱因斯坦分布的多相模拟退火在蛋白质折叠问题中的应用。

Q1 Biochemistry, Genetics and Molecular Biology Advances in Bioinformatics Pub Date : 2016-01-01 Epub Date: 2016-06-20 DOI:10.1155/2016/7357123
Juan Frausto-Solis, Ernesto Liñán-García, Juan Paulo Sánchez-Hernández, J Javier González-Barbosa, Carlos González-Flores, Guadalupe Castilla-Valdez
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引用次数: 5

摘要

提出了一种基于玻尔兹曼分布和玻色-爱因斯坦分布的混合多相模拟退火算法(MPSABBE)。MPSABBE设计用于解决蛋白质折叠问题(PFP)实例。这种新方法有四个阶段:(i)多淬火阶段(MQP), (ii)玻尔兹曼退火阶段(BAP), (iii)玻色-爱因斯坦退火阶段(BEAP)和(iv)动态平衡阶段(DEP)。BAP和BEAP分别是基于Boltzmann和Bose-Einstein分布的模拟退火搜索过程。DEP也是一种模拟退火搜索程序,应用于第四相的最终温度,这可以看作是第二个玻色-爱因斯坦相。MQP是一个搜索过程,范围从极高到高温,应用非常快的冷却过程,并且对接受新的解决方案没有很大的限制。然而,BAP和BEAP的温度范围分别从高到低和从低到极低。他们对接受新的解决方案更有限制。DEP在执行过程中使用一种特殊的启发式方法,通过应用最小二乘法来检测随机均衡。MPSABBE参数采用一种分析方法进行调优,该方法考虑了问题实例的最大和最小恶化。MPSABBE用几个PFP实例进行了测试,表明在经典SA上使用两种分布比仅使用玻尔兹曼分布更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Multiphase Simulated Annealing Based on Boltzmann and Bose-Einstein Distribution Applied to Protein Folding Problem.

A new hybrid Multiphase Simulated Annealing Algorithm using Boltzmann and Bose-Einstein distributions (MPSABBE) is proposed. MPSABBE was designed for solving the Protein Folding Problem (PFP) instances. This new approach has four phases: (i) Multiquenching Phase (MQP), (ii) Boltzmann Annealing Phase (BAP), (iii) Bose-Einstein Annealing Phase (BEAP), and (iv) Dynamical Equilibrium Phase (DEP). BAP and BEAP are simulated annealing searching procedures based on Boltzmann and Bose-Einstein distributions, respectively. DEP is also a simulated annealing search procedure, which is applied at the final temperature of the fourth phase, which can be seen as a second Bose-Einstein phase. MQP is a search process that ranges from extremely high to high temperatures, applying a very fast cooling process, and is not very restrictive to accept new solutions. However, BAP and BEAP range from high to low and from low to very low temperatures, respectively. They are more restrictive for accepting new solutions. DEP uses a particular heuristic to detect the stochastic equilibrium by applying a least squares method during its execution. MPSABBE parameters are tuned with an analytical method, which considers the maximal and minimal deterioration of problem instances. MPSABBE was tested with several instances of PFP, showing that the use of both distributions is better than using only the Boltzmann distribution on the classical SA.

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Advances in Bioinformatics
Advances in Bioinformatics Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (miscellaneous)
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