MLinvitroTox reloaded for high-throughput hazard-based prioritization of high-resolution mass spectrometry data

MLinvitroTox reloaded for high-throughput hazard-based prioritization of high-resolution mass spectrometry data

Abstract MLinvitroTox is an automated Python pipeline developed for high-throughput hazard-driven prioritization of toxicologically relevant signals detected in complex environmental samples through high-resolution tandem mass spectrometry (HRMS/MS). MLinvitroTox is a machine learning (ML) framework...

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Bibliographic Details
Main Authors: Katarzyna Arturi, Eliza J. Harris, Lilian Gasser, Beate I. Escher, Georg Braun, Robin Bosshard, Juliane Hollender
Format: Article
Language:English
Published: BMC 2025-01-01
Series:Journal of Cheminformatics
Subjects:
ToxCast
Tox21
Toxicity
In vitro assay
Activity prediction
HRMS/MS
Online Access:https://doi.org/10.1186/s13321-025-00950-4
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