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Predictive andmechanisticmultivariate linearregression models forreaction development Celine B. SantiagoJing-Yao GuoMatthew S. Sigman2018 год

Predictive and mechanistic multivariate linear regression models for reaction development
review

Полный текстСтраница публикацииПубликация в OpenAlex
Аннотация: The utilization of physical organic molecular descriptors for the quantitative description of reaction outcomes in multivariate linear regression models is demonstrated as an effective tool fora prioriprediction and mechanistic interrogation.
Год издания: 2018
Авторы: Celine B. Santiago, Jing-Yao Guo, Matthew S. Sigman
Издательство: Royal Society of Chemistry
Источник: Chemical Science
Ключевые слова: Computational Drug Discovery Methods, Machine Learning in Materials Science, Asymmetric Hydrogenation and Catalysis
Другие ссылки: Chemical Science (PDF)
Chemical Science (HTML)
OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (HTML)
Europe PMC (PubMed Central) (PDF)
Europe PMC (PubMed Central) (HTML)
PubMed Central (HTML)
PubMed (HTML)