Non-linearity of Metabolic Pathways Critically Influences the Choice of Machine Learning Model

Non-linearity of Metabolic Pathways Critically Influences the Choice of Machine Learning Model

The use of machine learning (ML) in life sciences has gained wide interest over the past years, as it speeds up the development of high performing models. Important modeling tools in biology have proven their worth for pathway design, such as mechanistic models and metabolic networks, as they allow...

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Bibliographic Details
Main Authors: Ophélie Lo-Thong-Viramoutou, Philippe Charton, Xavier F. Cadet, Brigitte Grondin-Perez, Emma Saavedra, Cédric Damour, Frédéric Cadet
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-06-01
Series:Frontiers in Artificial Intelligence
Subjects:
artificial intelligence
machine learning
non-linear modeling
drug target identification
Trypanosoma cruzi detoxification pathway
Entamoeba histolytica glycolysis pathway
Online Access:https://www.frontiersin.org/articles/10.3389/frai.2022.744755/full

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https://www.frontiersin.org/articles/10.3389/frai.2022.744755/full

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