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MLAGO: machine learning-aided global optimization for Michaelis constant estimation of kinetic modeling

Abstract Background Kinetic modeling is a powerful tool for understanding the dynamic behavior of biochemical systems. For kinetic modeling, determination of a number of kinetic parameters, such as the Michaelis constant (Km), is necessary, and global optimization algorithms have long been used for...

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Principais autores: Kazuhiro Maeda, Aoi Hatae, Yukie Sakai, Fred C. Boogerd, Hiroyuki Kurata
Format: Artigo
Sprog:Inglês
Udgivet: BMC 2022-11-01
Serier:BMC Bioinformatics
Fag:
Simulation
Michaelis constant
Kinetic modeling
Parameter estimation
Machine learning
Global optimization
Online adgang:https://doi.org/10.1186/s12859-022-05009-x
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