基于基因表达式编程预测醛类化合物急性毒性  被引量:5

Gene Expression Programming for Prediction of Acute Toxicity of Aldehydes

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作  者:张克俊[1] 孙守迁[1] 唐勇波[2] 司宏宗[3] 

机构地区:[1]浙江大学计算机科学与技术学院,杭州310027 [2]江西宜春学院,宜春336000 [3]青岛大学计算机与工程技术研究中心,青岛266071

出  处:《分析化学》2009年第3期425-428,共4页Chinese Journal of Analytical Chemistry

基  金:国家自然科学基金(No.60475025);教育部博士点基金(No.20050335096)资助项目

摘  要:对大鼠急性毒性的定量构效关系模型提出了一种新的算法:基因表达式编程,其核心是种群的进化。种群由染色体构成,染色体是由结构正确的基因组合而成,包含头部和尾部,对种群中染色体的基因进行特定的操作便形成了进化。本实验以启发式方法筛选的8个关键描述符为建模参数,应用基因表达式编程建立了88种醛类化合物分子结构对大鼠急性毒性的定量构效关系模型,模型交互检验相关系数为0.947,均方误差为0.037。通过与支持向量机方法的比较表明:基因表达式编程建立的定量构效关系模型能够更好地预测醛类化合物对大鼠急性毒性的半效致死量,且具有较强的稳定性。A novel way for building quantitative structure activity relationship (QSAR) model to predict the toxicity of aldehydes for rat was presented. A novel algorithm Gene Expression Programming (GEP) was utilized. GEP uses character linear chromosomes composed of genes structurally organized in a head and a tail. The chromosomes function as a genome and are subjected to modification by means of different operators. The chromosomes encode expression trees which are the object of selection. The rat lethal dose 50% (LD50) of 88 diverse aldehydes was modeled using the descriptors calculated from the molecular structure alone using a quantitative structure-activity relationship technique. Gene Expression programming (GEP) was utilized to construct the linear and nonlinear prediction models, leading to a good cross-validation correlation coefficient ( R2 ) of 0. 947 and root mean square errors ( S2 ) of 0. 037. The prediction results of the nonlinear GEP model seem to be better than those of support vector machine ( SVM). The GEP may offer new possibilities for solving more complex technological and scientific problems.

关 键 词:定量构效关系  半效致死量 支持向量机 基因表达式编程 

分 类 号:X174[环境科学与工程—环境科学]

 

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