A review of asthma and immunololgic mathematical models

Junehyuk Lee

doi:10.4168/aard.2017.5.3.123

Journal List > Allergy Asthma Respir Dis > v.5(3) > 1059244

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Lee: A review of asthma and immunololgic mathematical models

Review

Allergy Asthma Respir Dis 2017;5(3):123-127.

Published online: 5 May 2017

DOI: https://doi.org/10.4168/aard.2017.5.3.123

A review of asthma and immunololgic mathematical models

Junehyuk Lee

Division of Respiratory and Allergy Medicine, Department of Internal Medicine, Soonchunhyang University College of Medicine, Soonchunhyang University Bucheon Hospital, Bucheon, Korea

Correspondence to: Junehyuk Lee https://orcid.org/0000-0003-3958-0172 Division of Respiratory and Allergy Medicine, Department of Internal Medicine, Soonchunhyang University Bucheon Hospital, 170 Jomaru-ro, Wonmi-gu, Bucheon 14584, Korea Tel: +82-32-621-5148, Fax: +82-32-621-5018, E-mail: junehyuk@schmc.ac.kr

Received 4 November 201616 December 2016 Accepted 5 January 2017

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Asthma and allergic disease are of multifactorial nature like most of the other diseases that clinicians are facing. To establish the disease nature and improve the treatment success rate, it is unavoidable to examine closely enormous clinical and biological data that have been accumulated during the last century. The expanding gap between basic research and clinical medicine demand a novel approach. System biology emerged to reduce this gap as an interdisciplinary and translational method, and integrated clinical and experimental data through bioinformatics and mathematical modeling. Mathematical modeling is the method that disassembles the system, interpret the complex relations concealed among elements, and then establish a comprehensive and testable new hypothesis for the complex phenomenon or disease. To this end, we review the mathematical models dealting with asthma and immunologic system.

Keywords: Mathematical model, Simulation, Clinical trial, Asthma, Immunology

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Fig. 1.

Two main approaches in system biology. “-omics” approach proceeds first with obtaining high-throughput data produced from clinical samples and followed by statistical inference using biostatistics. A mathematical modeling proceeds first with a reconstruction of biochemical network based on published information, experimental data, and hypothesis that is relevant a given disease, then translates a mathematical model followed by using a model to prove hypotheses about the network regulation. Adapted from Sittka A, et al. Pediatr Res 2013;73:543-52.⁴

Fig. 2.

Levels of modelling. Biological simulation can be started from either the ‘bottom’ or the ‘top.’ Alternatively, it can be started from the ‘middle,’ which starts at any level (pathways, organelles, cells, tissues, organs or systems) at which there are sufficient data and reaches (up, down, and across) towards other levels and components. Adapted from Noble D. Nat Rev Mol Cell Biol 2002;3: 459-63.¹

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