5 papers
An efficient and flexible generalization of transit compartment models for delayed biological processes
Giulia Belluccini, Christiaan H. van Dorp, Linjie Huang +3
Transit compartment models are widely used in pharmacokinetics/pharmacodynamics to represent delayed biological processes such as absorption, maturation, cellular proliferation, an…
Frequentist and Bayesian population pharmacometrics: similarities, differences, and practical implications
Jodie A. Cochrane, Haini Wen, Liang Yang +2
Although the frequentist versus Bayesian debate has a long-standing history, and both are well-established approaches for inference, they are often considered separately in pharmac…
Hyperparameter selection for equation learning with biologically-informed neural networks
William Lavery, Jodie A. Cochrane, John T. Nardini +1
Biologically-informed neural networks (BINNs) have emerged as a flexible subclass of physics-informed neural networks (PINNs) for learning terms in partial differential equations f…
Physics-Informed Neural Networks for Biological Reaction-Diffusion Systems
William Lavery, Jodie A. Cochrane, Christian Olesen +3
Physics-informed neural networks (PINNs) provide a powerful framework for learning governing equations of dynamical systems from data. Biologically-informed neural networks (BINNs)…
A practical introduction to ODE modelling in Stan for biological systems
Sara Hamis, John Forslund, Cici Chen Gu +1
Integrating dynamical systems models with time series data is a central part of contemporary mathematical biology. With the rich variety of available models and data, numerous meth…