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Issue 5, 2019
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Towards rapid prediction of drug-resistant cancer cell phenotypes: single cell mass spectrometry combined with machine learning

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Abstract

Combined single cell mass spectrometry and machine learning methods is demonstrated for the first time to achieve rapid and reliable prediction of the phenotype of unknown single cells based on their metabolomic profiles, with experimental validation. This approach can be potentially applied towards prediction of drug-resistant phenotypes prior to chemotherapy.

Graphical abstract: Towards rapid prediction of drug-resistant cancer cell phenotypes: single cell mass spectrometry combined with machine learning

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Supplementary files

Article information


Submitted
17 Oct 2018
Accepted
29 Nov 2018
First published
29 Nov 2018

Chem. Commun., 2019,55, 616-619
Article type
Communication
Author version available

Towards rapid prediction of drug-resistant cancer cell phenotypes: single cell mass spectrometry combined with machine learning

R. Liu, G. Zhang and Z. Yang, Chem. Commun., 2019, 55, 616
DOI: 10.1039/C8CC08296K

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