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

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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Bibliographic Details
Main Authors: Kazuhiro Maeda, Aoi Hatae, Yukie Sakai, Fred C. Boogerd, Hiroyuki Kurata
Format: Article
Language:English
Published: BMC 2022-11-01
Series:BMC Bioinformatics
Subjects:
Simulation
Michaelis constant
Kinetic modeling
Parameter estimation
Machine learning
Global optimization
Online Access:https://doi.org/10.1186/s12859-022-05009-x

Internet

https://doi.org/10.1186/s12859-022-05009-x

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