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

Summary Kinetic 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 implementation RCGAToolbox is available from under GNU GPLv3, with application examples. The user guide is provided in the Supplementary Material. RCGAToolbox runs on MATLAB in Windows, Linux, and macOS. Contact kmaeda{at}bio.kyutech.ac.jp Supplementary information Supplementary Material is available at Bioinformatics online. ### Competing Interest Statement The authors have declared no competing interest.