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基于改进贝叶斯优化算法预测蛋白质残基可溶性
引用本文:王建. 基于改进贝叶斯优化算法预测蛋白质残基可溶性[J]. 四川理工学院学报(自然科学版), 2009, 22(3): 71-73
作者姓名:王建
作者单位:内江师范学院计算机科学学院,四川,内江,641112
基金项目:四川省教育厅项目,泸州老窖集团股份有限公司科研基金 
摘    要:蛋白质的残基相对可溶性表征蛋白质残基在三级结构中与溶剂接触的程度,它反映蛋白质三级结构及功能位点的主要特征。文章通过引入免疫算法中的亲和度和浓度概念,提出了一种改进贝叶斯优化算法,形成了贝叶斯优化算法选择局部残基相对可溶性优化依据。利用改进贝叶斯优化算法对2148条蛋白链进行分类实验,分析了窗宽对结果的影响,计算了三组数据在最佳参数状态下平均预测精度为79.7%。与其它方法相比,从结果来看,改进贝叶斯优化算法具有更好分类预测性能。

关 键 词:贝叶斯优化算法  蛋白质残基  可溶性  预测

Prediction of Protein Residue Solvent Accessibility Based On Improved Bayesian Optimization Algorithm
WANG Jian. Prediction of Protein Residue Solvent Accessibility Based On Improved Bayesian Optimization Algorithm[J]. Journal of Sichuan University of Science & Engineering(Natural Science Editton), 2009, 22(3): 71-73
Authors:WANG Jian
Affiliation:School of Computer and Information Science;Neijiang Normal University;Neijiang 641112;China
Abstract:Characterization of protein residue solvent accessibility is reflected in the solvent exposure of the 3D structures of biological protein.An improved Bayesian optimization algorithm has been put forward by introduced concept of affinity degree and concentration of immune algorithm.The optimization of relative solvent accessibility to select local residues has been formed.The classification experiment of 2148 protein chains has been completed with improved Bayesian optimization algorithm.The affection of win...
Keywords:Bayesian optimization algorithm  protein residues  solubility  prediction  
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