Related Experiment Video
Updated: Feb 10, 2026

Chronic, Acute, and Reactivated HIV Infection in Humanized Immunodeficient Mouse Models
Published on: December 3, 2019
Differential equation modeling of HIV viral fitness experiments: model identification, model selection, and
Hongyu Miao1, Carrie Dykes, Lisa M Demeter
1Department of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, 601 Elmwood Avenue, Box 630, Rochester, New York 14642, USA.
Abstract:
Many biological processes and systems can be described by a set of differential equation (DE) models. However, literature in statistical inference for DE models is very sparse. We propose statistical estimation, model selection, and multimodel averaging methods for HIV viral fitness experiments in vitro that can be described by a set of nonlinear ordinary differential equations (ODE). The parameter identifiability of the ODE models is also addressed. We apply the proposed methods and techniques to experimental data of viral fitness for HIV-1 mutant 103N. We expect that the proposed modeling and inference approaches for the DE models can be widely used for a variety of biomedical studies.
Related Concept Videos
Modeling with Differential Equations
Exponential Equations for Modeling Growth
Induced-fit Model
Enzymes exhibit substrate specificity, meaning that they can only bind to certain substrates. This is mainly determined by the shape and chemical...
Pharmacokinetic Models: Comparison and Selection Criterion
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Molecular Models
The Quantum-Mechanical Model of an Atom

