Predictive and mechanistic multivariate linear regression models for reaction development

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 int...

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Detalles Bibliográficos
Autores principales: Santiago, Celine B., Guo, Jing-Yao, Sigman, Matthew S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Royal Society of Chemistry 2018
Materias:
Chemistry
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5903422/
https://www.ncbi.nlm.nih.gov/pubmed/29719711
http://dx.doi.org/10.1039/c7sc04679k
Descripción
Sumario: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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