Leveraging artificial intelligence to advance the understanding of chemical neurotoxicity

Neurotoxicology is a specialty that aims to understand and explain the impact of chemicals, xenobiotics and physical conditions on nervous system function throughout the life span. Herein, we point to the need for integration of novel translational bioinformatics and chemo-informatics approaches, su...

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Bibliographic Details
Published in:Neurotoxicology (Park Forest South) 2022-03, Vol.89, p.9-11
Main Authors: Aschner, Michael, Mesnage, Robin, Docea, Anca Oana, Paoliello, Monica Maria Bastos, Tsatsakis, Aristides, Giannakakis, Georgios, Papadakis, Georgios Z., Vinceti, Silvio Roberto, Santamaria, Abel, Skalny, Anatoly V., Tinkov, Alexey A.
Format: Article
Language:English
Subjects:
Artificial Intelligence
Bioinformatics
Commentary
Genetic variability
Life span
Machine learning
Nervous system
Neurotoxicity
Xenobiotics
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Summary:Neurotoxicology is a specialty that aims to understand and explain the impact of chemicals, xenobiotics and physical conditions on nervous system function throughout the life span. Herein, we point to the need for integration of novel translational bioinformatics and chemo-informatics approaches, such as machine learning (ML) and artificial intelligence (AI) to the discipline. Specifically, we advance the notion that AI and ML will be helpful in identifying neurotoxic signatures, provide reliable data in predicting neurotoxicity in the context of genetic variability, and improve the understanding of neurotoxic outcomes associated with exposures to mixtures, to name a few.
ISSN:0161-813X
1872-9711
DOI:10.1016/j.neuro.2021.12.007