Computational framework to integrate the effect of antigen recognition on disease epidemiology outcome: multi-scale approach

Mukherjee, Sumanta and Chandra, Nagasuma (2013) Computational framework to integrate the effect of antigen recognition on disease epidemiology outcome: multi-scale approach. In: 4th Annual ORNL Biomedical Sciences and Engineering Conference on Collaborative Biomedical Innovations, MAY 21-23, 2013, Biomed Sci & Engn Ctr, Oak Ridge Natl Lab, Oak Ridge, TN Date: MAY 21-23, 2013 .

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Abstract

Human Leukocyte Antigen (HLA) plays an important role, in presenting foreign pathogens to our immune system, there by eliciting early immune responses. HLA genes are highly polymorphic, giving rise to diverse antigen presentation capability. An important factor contributing to enormous variations in individual responses to diseases is differences in their HLA profiles. The heterogeneity in allele specific disease responses decides the overall disease epidemiological outcome. Here we propose an agent based computational framework, capable of incorporating allele specific information, to analyze disease epidemiology. This framework assumes a SIR model to estimate average disease transmission and recovery rate. Using epitope prediction tool, it performs sequence based epitope detection for a given the pathogenic genome and derives an allele specific disease susceptibility index depending on the epitope detection efficiency. The allele specific disease transmission rate, that follows, is then fed to the agent based epidemiology model, to analyze the disease outcome. The methodology presented here has a potential use in understanding how a disease spreads and effective measures to control the disease.

Item Type:	Conference Proceedings
Additional Information:	Copy right for this article belongs to the IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Department/Centre:	Division of Physical & Mathematical Sciences > Mathematics
Date Deposited:	10 Oct 2014 09:15
Last Modified:	16 Oct 2014 08:22
URI:	http://eprints.iisc.ac.in/id/eprint/50000

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