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Solving Two-Dimensional HP Model by Firefly Algorithm and Simplified Energy Function

机译：用萤火虫算法和简化能量函数求解二维HP模型

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摘要

In order to solve the HP model of the protein folding problem, we investigated traditional energy function and pointed out that its discrete property cannot give direction of the next step to the searching point, causing a challenge to optimization algorithms. Therefore, we introduced the simplified energy function into a turn traditional discrete energy function to continuous one. The simplified energy function totals the distance between all pairs of hydrophobic amino acids. To optimize the simplified energy function, we introduced the latest swarm intelligence algorithm, the firefly algorithm (FA). FA is a hot nature-inspired technique and has been used for solving nonlinear multimodal optimization problems in dynamic environment. We also proposed the code scheme strategy to apply FA to the simplified HP model with the clash test strategy. The experiment took 14 sequences of different chain lengths from 18 to 100 as the dataset and compared the FA with standard genetic algorithm and immune genetic algorithm. Each algorithm ran 20 times. The averaged energy convergence results show that FA achieves the lowest values. It concludes that it is effective to solve 2D HP model by the firefly algorithm and the simplified energy function.
机译：为了解决蛋白质折叠问题的HP模型，我们研究了传统的能量函数，并指出其离散特性无法将下一步的方向指示到搜索点，从而给优化算法带来了挑战。因此，我们将简化的能量函数引入了从传统的离散能量函数到连续函数的转变。简化的能量函数可计算所有疏水氨基酸对之间的距离。为了优化简化的能量函数，我们引入了最新的群体智能算法，萤火虫算法（FA）。 FA是一种受自然启发的热门技术，已用于解决动态环境中的非线性多峰优化问题。我们还提出了代码方案策略，以通过冲突测试策略将FA应用于简化的HP模型。实验以18至100的14条不同链长的序列作为数据集，并将FA与标准遗传算法和免疫遗传算法进行了比较。每个算法运行20次。平均能量收敛结果表明，FA达到最低值。结论是利用萤火虫算法和简化的能量函数求解二维HP模型是有效的。

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  • 来源
    《Mathematical Problems in Engineering》 |2013年第1期|398141.1-398141.9|共9页
  • 作者

    Yudong Zhang; Lenan Wu; Shuihua Wang;

  • 作者单位

    School of Information Science and Engineering, Southeast University, Nanjing, Jiangsu 210096, China;

    School of Information Science and Engineering, Southeast University, Nanjing, Jiangsu 210096, China;

    Grover School of Engineering, The City College of New York, New York, NY 10031, USA;

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