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基于集成学习算法构建有机化学品鱼体生物富集因子的QSAR预测模型 被引量:10
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作者 丁蕊 陈景文 +4 位作者 于洋 林军 王中钰 唐伟豪 李雪花 《环境化学》 CAS CSCD 北大核心 2021年第5期1295-1304,共10页
生物富集因子(BCF)是评价化学品生物累积能力的重要参数。目前全球市场上使用的化学品数量已超过了35万种,但是只有一千多种化学品具有BCF值。定量构效关系(QSAR)模型被认为是一种有效填补数据空缺的方法。目前大多数预测BCF的QSAR模型... 生物富集因子(BCF)是评价化学品生物累积能力的重要参数。目前全球市场上使用的化学品数量已超过了35万种,但是只有一千多种化学品具有BCF值。定量构效关系(QSAR)模型被认为是一种有效填补数据空缺的方法。目前大多数预测BCF的QSAR模型为单一模型,而集成模型可能会对BCF的预测效果有所改进。本研究建立了一个全面的鱼类BCF数据库,涵盖1300多种有机化学品的BCF实测值。基于此数据库,依据QSAR模型构建和验证导则,使用多种机器学习算法建立了预测鱼类BCF的5种单一模型和11种集成模型。结果表明,与单一模型相比,集成模型具有更好的拟合能力、稳健性、预测准确性以及更广泛的应用域。进一步使用最优集成模型对《中国现有化学物质清单》(IECSC)中化学物质的BCF进行了预测,结果表明该清单中有1066种化学物质具有生物累积性,86种化学物质具有强生物累积性。本研究所构建的模型可为化学品生物累积能力评估提供必要数据,支持化学品风险评价与管理工作。 展开更多
关键词 生物富集因子 定量构效关系 机器学习 集成模型 应用域
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Prediction model on hydrolysis kinetics of phthalate monoester:A density functional theory study
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作者 Tong Xu Jingwen Chen +4 位作者 Deming Xia weihao tang Jiansheng Cui Chun Liu Shuangjiang Li 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2024年第1期51-58,共8页
As primary degradation products of phthalate esters,phthalate monoesters(MPEs)have been widely detected in various aquatic environments and drawn growing toxicological concerns.Hydrolysis kinetics that is of importanc... As primary degradation products of phthalate esters,phthalate monoesters(MPEs)have been widely detected in various aquatic environments and drawn growing toxicological concerns.Hydrolysis kinetics that is of importance for assessing environmental persistence of chemicals remain elusive for MPEs.Herein,kinetics of base-catalyzed and neutral hydrolysis for 18 MPEs with different leaving groups was investigated by density functional theory calculation.Results indicate that MPEs with leaving groups having p Kaof<10 prefer dissociative transition states.MPEs are more persistent than their parents,and their hydrolysis half-lives were calculated to vary from 3.4 min to 79.2 years(p H=7–9).A quantitative structure-activity relationship model was developed for predicting the hydrolysis kinetics parameters.It was found that p Kaof the leaving groups and electronegativity of the MPEs are key factors determining the hydrolysis kinetics.This work may lay a theoretical foundation for better understanding the chemical process that governs MPE persistence in aquatic environments. 展开更多
关键词 Phthalate monoesters Phthalate esters HYDROLYSIS Density functional theory Quantitative structure-activity RELATIONSHIP
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Novel quantitative structure activity relationship models for predicting hexadecane/air partition coefficients of organic compounds
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作者 Ya Wang weihao tang +4 位作者 Zijun Xiao Wenhao Yang Yue Peng Jingwen Chen Junhua Li 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2023年第2期98-104,共7页
Predicting the logarithm of hexadecane/air partition coefficient(L)for organic compounds is crucial for understanding the environmental behavior and fate of organic compounds and developing prediction models with poly... Predicting the logarithm of hexadecane/air partition coefficient(L)for organic compounds is crucial for understanding the environmental behavior and fate of organic compounds and developing prediction models with polyparameter linear free energy relationships.Herein,two quantitative structure activity relationship(QSAR)models were developed with 1272 L values for the organic compounds by using multiple linear regression(MLR)and support vector machine(SVM)algorithms.On the basis of the OECD principles,the goodness of fit,robustness and predictive ability for the developed models were evaluated.The SVM model was first developed,and the predictive capability for the SVM model is slightly better than that for the MLR model.The applicability domain(AD)of these two models has been extended to include more kinds of emerging pollutants,i.e.,oraganosilicon compounds.The developed QSAR models can be used for predicting L values of various organic compounds.The van derWaals interactions between the organic compound and the hexadecane have a significant effect on the L value of the compound.These in silico models developed in current study can provide an alternative to experimental method for high-throughput obtaining L values of organic compounds. 展开更多
关键词 L value Quantitative structure-activity RELATIONSHIP Multiple linear regression Support vector machine Oraganosilicon compounds
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