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bioRxiv · 10.1101/2021.02.15.431062

RCGAToolbox: A real-coded genetic algorithm software for parameter estimation of kinetic models

Maeda, K.·Boogerd, F. C.·Kurata, H.
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Abstract

SummaryKinetic modeling is essential in understanding the dynamic behavior of biochemical networks, such as metabolic and signal transduction pathways. However, parameter estimation remains a major bottleneck in the development of kinetic models. We present RCGAToolbox, software for real-coded genetic algorithms (RCGAs), which accelerates the parameter estimation of kinetic models. RCGAToolbox provides two RCGAs: the unimodal normal distribution crossover with minimal generation gap (UNDX/MGG) and real-coded ensemble crossover star with just generation gap (REXstar/JGG), using the stochastic ranking method. The RCGAToolbox also provides user-friendly graphical user interfaces. Availability and implementationRCGAToolbox is available from https://github.com/kmaeda16/RCGAToolbox under GNU GPLv3, with application examples. The user guide is provided in the Supplementary Material. RCGAToolbox runs on MATLAB in Windows, Linux, and macOS. Contactkmaeda@bio.kyutech.ac.jp Supplementary informationSupplementary Material is available at Bioinformatics online.

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Maeda, K., Boogerd, F. C., Kurata, H.. 2021-02-16. RCGAToolbox: A real-coded genetic algorithm software for parameter estimation of kinetic models. https://doi.org/10.1101/2021.02.15.431062

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