Machine learning-empowered <i>cis</i>-diol metabolic fingerprinting enables precise diagnosis of primary liver cancer-Reference-Cited by-同舟云学术

Machine learning-empowered cis-diol metabolic fingerprinting enables precise diagnosis of primary liver cancer

Published:2023 Issue:10 Volume:14 Page:2553-2561
ISSN:2041-6520
Container-title:Chemical Science
language:en
Short-container-title:Chem. Sci.

Author:

Li Pengfei¹,Xu Shuxin¹,Han Yanjie¹,He Hui¹,Liu Zhen¹^ORCID

Affiliation:

1. State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, 163 Xianlin Avenue, Nanjing 210023, China

Abstract

A mass spectrometric platform was built for in-depth profiling of mutational landscape of cis-diol metabolites from the healthy to primary liver cancer (PLC) patients. This method enabled more precise PLC diagnosis than protein marker-based methods.

Funder

National Natural Science Foundation of China

Nanjing University

Ministry of Science and Technology of the People's Republic of China

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2023/SC/D2SC05541D

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1. Detecting RNA modifications in the epitranscriptome: predict and validate