Abstract
Lymphocyte recirculation plays an important role in controlling the spread of both pathogenic infections and tumor-producing cancer cells in the human body. We present a mathematical and computational framework that allows investigation of recirculating lymphocytes and estimation of model parameters using a genetic algorithm. The framework allows estimating parameters using data obtained from experiments performed in laboratory studies of rats as well as clinical studies of human subjects. Our computational model allows improved understanding of these data. Mathematical models enable investigators to obtain a quantitative picture of immune system kinetics and diversity in human health and disease outcomes. Our data-driven systems biology and immunological modeling approach contributes to a growing understanding of the dynamics of lymphocyte recirculation.
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