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Towards rapid prediction of drug-resistant cancer cell phenotypes: single cell mass spectrometry combined with machine learning†
Chemical Communications ( IF 4.3 ) Pub Date : 2018-11-29 00:00:00 , DOI: 10.1039/c8cc08296k
Renmeng Liu 1, 2, 3, 4 , Genwei Zhang 1, 2, 3, 4 , Zhibo Yang 1, 2, 3, 4
Affiliation  

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.

中文翻译:

快速预测耐药性癌细胞表型:单细胞质谱结合机器学习

首次展示了结合单细胞质谱和机器学习方法的方法,该方法可以基于未知单细胞的代谢组学特征快速,可靠地预测其表型,并进行实验验证。该方法可潜在地用于预测化学疗法之前的耐药表型。
更新日期:2018-11-29
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