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A stochastic model of B cell affinity maturation for dengue infections

DESCRIPTION:

Stochastic model of the immune response to dengue infections and effect of vaccination. This model is designed to simulate the human response of B cell and T cells to the dengue virus and to the polyvalent live-attenuated vaccine constructs. The immune system is modeled as a system of chemical reactions using the Gillespie algorithm (Woo & Reifman, Proc Nat Acad Sci USA, 2012). It uses the immune shape space model developed by Smith et al. (Smith et al., J Theor Biol 1997) and the immune response model by B cells for malaria by Chaudhury et al. (Journal of Immunology. 2014).

REQUIREMENTS: The immune modeling code requires Python 2.4 or later.

USAGE EXAMPLES:

Natural infections:

python run_dengueinfections.py <data_file> monovalent

python run_dengueinfections.py <data_file> polyvalent

Vaccine studies:

python run_infectvaccine_vaccineDENV2.py <data_file> polyvalent monovalent

python run_infectvaccine_3vaccinesDENV2.py <data_file> polyvalent monovalent

CITATION:

Nguyen et al. Stochastic models of the adaptive immune response predict disease severity and captures enhanced cross-reactivity in natural dengue infections. Journal of Immunology. 2021

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Stochastic model of the immune response to dengue infections

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