Number of identified metabolites for each dataset, considering the algorithm, incubation conditions, and acquisition mode (in case of dataset-3).

Number of identified metabolites for each dataset, considering the algorithm, incubation conditions, and acquisition mode (in case of dataset-3).

<p>Number of identified metabolites for each dataset, considering the algorithm, incubation conditions, and acquisition mode (in case of dataset-3).</p>

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Bibliographic Details
Main Author: Paula Cifuentes (22050278) (author)
Other Authors: Ismael Zamora (2385154) (author), Tatiana Radchenko (4559779) (author), Fabien Fontaine (75372) (author), Albert Garriga (22050281) (author), Luca Morettoni (4559788) (author), Jesper Kammersgaard Christensen (22050284) (author), Hans Helleberg (12980035) (author), Bridget A. Becker (2412181) (author)
Published: 2025
Subjects:
Biochemistry
Cancer
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
significant challenges persist
molecular weight range
enables clear localization
distinct fragmentation strategies
associated computational demands
700 &# 8211
automated liquid chromatography
instilling greater confidence
improved various stages
exploring metabolic susceptibility
enhanced visualization capabilities
small molecules metid
resolution mass spectrometry
data analysis applicable
advancing automated metid
macromolecules using high
level ), non
data analysis
automated software
visualization algorithm
various experimental
metabolic biotransformations
level ),
greater number
monoisotopic mass
abundant mass
xlink ">
unnatural monomers
structural complexity
previous studies
peptides ).
metabolite structures
metabolite identification
macromolecules due
ionization conditions
hybrid mode
drug metabolism
drug development
degradation products
cyclic peptides
consistent detection
comprising linear
comprehensive understanding
compound procurement
commonly used
bond notation
accurate prediction
970 metabolites
7630 da
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