Inverse problem of HIV cell dynamics using Genetic Algorithms

8th International Congress of Engineering Physics

物理学;工业技术

González, J.A.^1 ; Guzmán, F.S.^1

Laboratorio de Inteligencia Artificial y Supercómputo, Instituto de Física y Matemáticas, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Mexico^1

关键词: Cell concentrations;    Cell dynamics;    Mutation rates;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/792/1/012070/pdf
DOI  :  10.1088/1742-6596/792/1/012070

学科分类：工业工程学

来源: IOP

【 摘 要 】

In order to describe the cell dynamics of T-cells in a patient infected with HIV, we use a flavour of Perelson's model. This is a non-linear system of Ordinary Differential Equations that describes the evolution of healthy, latently infected, infected T-cell concentrations and the free viral cells. Different parameters in the equations give different dynamics. Considering the concentration of these types of cells is known for a particular patient, the inverse problem consists in estimating the parameters in the model. We solve this inverse problem using a Genetic Algorithm (GA) that minimizes the error between the solutions of the model and the data from the patient. These errors depend on the parameters of the GA, like mutation rate and population, although a detailed analysis of this dependence will be described elsewhere.