On the computational modeling of the innate immune system

BMC Bioinformatics

Proceedings

Gilson Costa Macedo¹  Rodrigo Weber dos Santos²  Alexandre Bittencourt Pigozzo²  Marcelo Lobosco² 

[1] Graduate Program in Biological Sciences, UFJF, Rua José Lourenço Kelmer, s/n - Campus Universitário, Bairro São Pedro, CEP: 36036-900, Juiz de Fora, MG, Brazil;Graduate Program in Computational Modeling, UFJF, Rua José Lourenço Kelmer, s/n -Campus Universitário, Bairro São Pedro, CEP: 36036-900, Juiz de Fora, MG, Brazil;

关键词: Innate Immune System;    Active Macrophage;    Adaptive Immune System;    Human Immune System;    Endothelium Permeability;   

DOI  :  10.1186/1471-2105-14-S6-S7

来源: Springer

【 摘 要 】

In recent years, there has been an increasing interest in the mathematical and computational modeling of the human immune system (HIS). Computational models of HIS dynamics may contribute to a better understanding of the relationship between complex phenomena and immune response; in addition, computational models will support the development of new drugs and therapies for different diseases. However, modeling the HIS is an extremely difficult task that demands a huge amount of work to be performed by multidisciplinary teams. In this study, our objective is to model the spatio-temporal dynamics of representative cells and molecules of the HIS during an immune response after the injection of lipopolysaccharide (LPS) into a section of tissue. LPS constitutes the cellular wall of Gram-negative bacteria, and it is a highly immunogenic molecule, which means that it has a remarkable capacity to elicit strong immune responses. We present a descriptive, mechanistic and deterministic model that is based on partial differential equations (PDE). Therefore, this model enables the understanding of how the different complex phenomena interact with structures and elements during an immune response. In addition, the model's parameters reflect physiological features of the system, which makes the model appropriate for general use.

【 授权许可】

CC BY   
© Pigozzo et al.; licensee BioMed Central Ltd. 2013