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Particle swarm optimization with backtracking in protein structure prediction problem

机译:粒子群优化与蛋白质结构预测问题的回溯

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Several population based search algorithms are developed by the researchers to predict the native state of protein from its primary sequences. The paper aims at predicting the native conformation of proteins in lattice model using PSO based searching method. However, stuck at local minima and generating illegal conformation are the main drawbacks of applying the search algorithm in protein structure prediction. Adaptive Polynomial Mutation (APM) is performed to remove local minima while illegal conformations are repaired using backtracking method. Benchmark sequences with different length are applied to verify the proposed algorithm showing better results compare to the earlier approaches.
机译:研究人员开发了几种基于群体的搜索算法,以预测来自其主要序列的蛋白质的天然状态。本文旨在使用基于PSO的搜索方法预测晶格模型中蛋白质的天然构象。然而,粘在局部最小值并产生非法构象是应用搜索算法在蛋白质结构预测中的主要缺点。进行自适应多项式突变(APM)以使用反向特性方法修复非法构象的同时进行局部最小值。应用具有不同长度的基准序列以验证所提出的算法,显示与前面方法相比的更好结果。

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