Exploratory machine-learned theoretical chemical shifts can closely predict metabolic mixture signals-Reference-Cited by-同舟云学术

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

Published:2018 Issue:43 Volume:9 Page:8213-8220
ISSN:2041-6520
Container-title:Chemical Science
language:en
Short-container-title:Chem. Sci.

Author:

Ito Kengo¹²³⁴⁵^ORCID,Obuchi Yuka⁴⁵²³,Chikayama Eisuke¹²³⁶⁷,Date Yasuhiro¹²³⁴⁵,Kikuchi Jun¹²³⁴⁵^ORCID

Affiliation:

1. RIKEN Center for Sustainable Resource Science

2. Yokohama

3. Japan

4. Graduate School of Medical Life Science

5. Yokohama City University

6. Department of Information Systems

7. Niigata University of International and Information Studies

Abstract

Exploratory machine-learned model can predict the experimental chemical shifts with high accuracy, and the corrected theoretical values can be used to assign NMR signals in molecular complexities.

Funder

Ministry of Agriculture, Forestry and Fisheries

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2018/SC/C8SC03628D

Reference32 articles.

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