Mathematical Biology Seminar

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17:00-18:00   Room #509 (Graduate School of Math. Sci. Bldg.)
Yuki Sugiyama (Institute of Industrial Science, The University of Tokyo)
Large deviation theory for age-structured population dynamics
[ Abstract ]
Control of population growth is ubiquitous problem in many fields. In the context of medical treatment, we attempt to diminish the growing speed of a cell population composed of cancer cells or pathogens by using antibiotics or some special therapies. In terms of evolutional biology, to survive in a fluctuating environment, cells maximize (optimize) their population growth by exploiting a risk hedge strategy for adaptation to the fluctuation. Recent development of experimental devices enables us to measure a big size lineage data that describes a growing cell population. In this study, by using these lineage data, we analyze a behavior of the population growth. Here, a structure of statistical mechanics using the large deviation theory plays an important role. As a results, we reveal that the population growth rate is given by the Legendre transform of the large deviation function for the semi-Markov process that describes a stochastic switch of cell types in the time evolution. Furthermore, by using this structure, we show that responses of the population growth rate with respect to an environmental change can be evaluated by statistics on a retrospective lineage path.