Selecting appropriate objective functions is a critical yet challenging step in fitting mathematical models to biological data, directly impacting parameter estimation accuracy, model predictive power, and ultimately, scientific and clinical...
This article provides a comprehensive guide to multi-start nonlinear least squares (NLS) implementation, specifically tailored for researchers and professionals in drug development.
This article provides a comprehensive guide to regularization techniques tailored for researchers, scientists, and professionals in drug development.
This article provides a comprehensive guide to Markov Chain Monte Carlo (MCMC) methods, tailored for researchers, scientists, and professionals in drug development.
This article provides a comprehensive guide to adjoint sensitivity analysis (ASA) for researchers, scientists, and drug development professionals working with large biological models.
This article provides a comprehensive exploration of genetic algorithms (GAs) applied to signaling pathway analysis in biomedical research.
This article provides a detailed guide for researchers and scientists on using PyBioNetFit (PyBNF), a powerful software tool for parameterizing biological models.
This comprehensive guide explores parameter estimation and uncertainty quantification using Data2Dynamics (D2D), an open-source MATLAB toolbox specifically designed for dynamic modeling of biological systems.
This article provides a comprehensive exploration of gradient-based optimization and sensitivity analysis, powerful computational techniques that are revolutionizing drug discovery.
Estimating parameters for dynamic models described by Ordinary Differential Equations (ODEs) is a critical yet challenging task in biomedical research, particularly in drug development and systems biology.