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Prof. Vitaly Ganusov
Texas Biomedical Research Institute
Texas, USA
Page :
https://www.txbiomed.org/scientists/vitaly-ganusov/
Mathematical modeling to guide experimental design: T cell clustering as a case study
Mathematical modeling provides a rigorous way to quantify immunological processes and to discriminate between alternative mechanisms driving specific biological phenomena. Mathematical models of immunological phenomena often are developed by modellers to explain specific sets of experimental data after the data have been collected by experimental collaborators. Whether the available data are sufficient to accurately estimate model parameters or to discriminate between alternative models is not typically investigated. Here I show how one can use mathematical modeling to define type and size of experimental data needed to accurately estimate model parameters (a.k.a., power analysis). I will use a case study of the kinetics of formation of clusters of T lymphocytes around malaria parasite-infected hepatocytes observed in livers of mice with microscopy. I illustrate how following the dynamics of T lymphocyte clusters around individual parasitized cells allows for more accurately estimate model parameters; however, such experiments are typically have a higher cost. Combining experimental design with mathematical modeling-driven power analyses should help design more effective experiments.
International Conference on
Computational
and
Mathematical Modelling
CONTACT US
Centre for Mathematical Modelling
Faculty of Science
University of Colombo
Colombo
Sri Lanka
Phone :
0112 782 828
Email :
cmm@maths.cmb.ac.lk
