Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics-Reference-Cited by-同舟云学术

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Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics

Published:2019-03-31 Issue:9 Volume:91 Page:5768-5776
ISSN:0003-2700
Container-title:Analytical Chemistry
language:en
Short-container-title:Anal. Chem.

Author:

Liu Zhichao¹,Portero Erika P.²,Jian Yiren¹,Zhao Yunjie³,Onjiko Rosemary M.²,Zeng Chen¹,Nemes Peter²^ORCID

Affiliation:

1. Department of Physics, The George Washington University, Washington, D.C. 20052, United States

2. Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland 20742, United States

3. Institute of Biophysics and Department of Physics, Central China Normal University, Wuhan, Hubei 430079, China

Funder

National Institute of General Medical Sciences

National Cancer Institute

Publisher

American Chemical Society (ACS)

Subject

Analytical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.analchem.8b05985

Reference40 articles.

1. Single-cell analysis at the threshold

2. Anionic metabolite profiling by capillary electrophoresis–mass spectrometry using a noncovalent polymeric coating. Orange juice and wine as case studies

3. Profiling metabolites and peptides in single cells

4. Progress toward single cell metabolomics

5. Single-cell analysis by ambient mass spectrometry

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