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Chemical Proportionality within Molecular Networks

delete2021-09-17
delete23
PRE
AI
D
Daniel Petras *
A
Andrés Mauricio Caraballo‐Rodríguez
A
Alan K. Jarmusch
C
Carlos Molina‐Santiago
J
Julia M. Gauglitz
E
Emily C. Gentry
P
Pedro Belda‐Ferre
D
Diego Romero
S
Shirley M. Tsunoda
P
Pieter C. Dorrestein
M
Mingxun Wang *
DOI:10.1021/acs.analchem.1c01520delete
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Abstract

Abstract

En 中文
Molecular networking of non-targeted tandem mass spectrometry data connects structurally related molecules based on similar fragmentation spectra. Here, we report the Chemical Proportionality (ChemProp) contextualization of molecular networks. ChemProp scores the changes of abundance between two connected nodes over sequential data series (e.g., temporal or spatial relationships), which can be displayed as a direction within the network to prioritize potential biological and chemical transformations or proportional changes of (biosynthetically) related compounds. We tested the ChemProp workflow on a ground truth data set of a defined mixture and highlighted the utility of the tool to prioritize specific molecules within biological samples, including bacterial transformations of bile acids, human drug metabolism, and bacterial natural products biosynthesis. The ChemProp workflow is freely available through the Global Natural Products Social Molecular Networking (GNPS) environment.
Keywords:
MASS-SPECTROMETRY
GENES
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Journal

Analytical Chemistry cover
Analytical Chemistry
IF:
6.7
Papers:
4.7W
Citations:
15.9W

Organization

University of California System cover
University of California System
Scholars:
37.5W
Papers: 33.7W
Citations: 6.6K
U
University of California San Diego
Scholars:
4.6W
Papers: 3.5W
Citations: 924