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化学学报
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化学学报 ›› 2012, Vol. 70 ›› Issue (08): 989-994.DOI: 10.6023/A1111083 上一篇    下一篇

研究论文

基于MOLMAP 指数的光化学反应分类预测

张庆友a, 冯秀林a, 龙海林a, 索净洁a, 张丹丹a, 许力壮b, 许禄c   

  1. a 河南大学化学化工学院环境与分析科学研究所 开封 475004;
    b 深圳市人民医院 深圳 518020;
    c 中国科学院长春应用化学研究所 长春 130022
  • 投稿日期:2011-11-08 修回日期:2012-01-20 发布日期:2012-01-31
  • 通讯作者: 许禄
  • 基金资助:

    国家自然科学基金(No. 20875022)、教育部留学回国人员科研启动基金和河南省国际科技合作项目(No. 114300510009)资助项目.

Classification Prediction of Photochemical Ractions Based on MOLMAP

Zhang Qingyoua, Feng Xiulina, Long Hailina, Suo Jingjiea, Zhang Dandana, Xu Lizhuangb, Xu Luc   

  1. a Institute of Environmental and Analytical Sciences, College of Chemistry and Chemical Engineering, Henan University, Kaifeng 475004;
    b Renmin Hospital of Shenzhen, Shenzhen 518020;
    c Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022
  • Received:2011-11-08 Revised:2012-01-20 Published:2012-01-31
  • Supported by:

    Project supported by the National Natural Science Foundation of China (No. 20875022), Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry and International Science and Technology Cooperation of Henan Province (No. 114300510009).

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由反应物和产物的结构衍生了反应物、产物和化学反应的MOLMAP 指数, 其中化合物的结构由化学键的物理化学性质和拓扑性质所表征. 将前述MOLMAP 指数应用于一个含七类光化学反应的数据集, 通过随机森林建立了三种类型的模型: (1)预测反应物可能发生的反应类型; (2)预测可能合成产物的反应类型; (3)预测整个化学反应的类型. 由于无需指定数据集中参与反应的化学键, 所以, MOLMAP 指数能够得到广泛的应用. 所得分类预测结果好于我们此前对同一数据集的研究, 表明改进化学键的描述有助于提高MOLMAP 指数的预测能力.

关键词: 光化学反应分类, MOLMAP 指数, Kohonen 自组织映射, 随机森林

In this article, MOLMAP (molecular maps of atom-level properties) descriptors of reactants, products and reactions were derived from the structures of reactants and products which were represented by physicochemical properties and topological properties of chemical bonds of the compounds. The MOLMAP descriptors above-mentioned were applied to a data set composed of seven classes of photochemical reactions, and three kinds of models were constructed by random forest: (1) The model to predict the type of reaction the reactants produce; (2) the model to predict the type of reaction from which the product can be synthesized; (3) the model to predict the type of the whole reactions. Because the specification of the bonds involved in the reactions was not required in data sets, the MOLMAP descriptors can be used widely. The results obtained in this article were better than those results in our previous researches for the same data set. Therefore, the modification of bond description is helpful for improving the prediction ability of MOLMAP descriptors.

Key words: photochemical reaction classification, MOLMAP AP descriptor, Kohonen SOM, random forest