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Exploratory machine-learned theoretical chemical shifts can closely predict metabolic mixture signals

Various chemical shift predictive methodologies have been studied and developed, but there remains the problem of prediction accuracy. Assigning the NMR signals of metabolic mixtures requires high predictive performance owing to the complexity of the signals. Here we propose a new predictive tool th...

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Detalles Bibliográficos
Autores principales: Ito, Kengo, Obuchi, Yuka, Chikayama, Eisuke, Date, Yasuhiro, Kikuchi, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Royal Society of Chemistry 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6240814/
https://www.ncbi.nlm.nih.gov/pubmed/30542569
http://dx.doi.org/10.1039/c8sc03628d