Predictive and mechanistic multivariate linear regression models for reaction development 论文

2018Chemical Science引用 427顶会

Computational Drug Discovery MethodsMachine Learning in Materials ScienceAsymmetric Hydrogenation and Catalysis

人工智能 Computational Drug Discovery Methods Machine Learning in Materials Science Asymmetric Hydrogenation and Catalysis

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Multivariate Linear Regression (MLR) models utilizing computationally-derived and empirically-derived physical organic molecular descriptors are described in this review. Several reports demonstrating the effectiveness of this methodological approach towards reaction optimization and mechanistic interrogation are discussed. A detailed protocol to access quantitative and predictive MLR models is provided as a guide for model development and parameter analysis.

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Matthew S. Sigman

Jing-Yao Guo

Celine B. Santiago

Predictive and mechanistic multivariate linear regression models for reaction development 论文

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