Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites-Reference-Cited by-同舟云学术

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Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites

Published:2017-09-15 Issue:19 Volume:89 Page:10397-10406
ISSN:0003-2700
Container-title:Analytical Chemistry
language:en
Short-container-title:Anal. Chem.

Author:

Mahieu Nathaniel G.¹^ORCID,Patti Gary J.¹^ORCID

Affiliation:

1. Department of Chemistry, Washington University, St. Louis, Missouri 63130, United States

Funder

National Institute of Environmental Health Sciences

National Cancer Institute

Camille and Henry Dreyfus Foundation

Pew Charitable Trusts

Publisher

American Chemical Society (ACS)

Subject

Analytical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.analchem.7b02380

Reference44 articles.

1. RAMClust: A Novel Feature Clustering Method Enables Spectral-Matching-Based Annotation for Metabolomics Data

2. Computational Metabolomics: A Framework for the Million Metabolome

3. MetaboAnalyst 3.0—making metabolomics more meaningful

4. Mass appeal: metabolite identification in mass spectrometry-focused untargeted metabolomics

5. Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling

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