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University of Cambridge > Talks.cam > DAMTP Statistical Physics and Soft Matter Seminar > Quantitative model inference for living matter
Quantitative model inference for living matterAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Michael te Vrugt. Recent advances in live-imaging techniques provide unprecedented dynamical data ranging from the cellular to the organism scale. Notwithstanding such experimental progress, quantitative theoretical models remain lacking, even for moderately complex classes of systems. Here, I will summarize our ongoing efforts to implement computational frameworks for inferring predictive ordinary differential equations (ODEs), stochastic differential equations (SDEs), and partial differential equations (PDEs) from multi-scale imaging data for biological systems. As specific examples, we will consider models for cell growth and division, neural dynamics, mosquito flight behavior, and collective animal swarming. This talk is part of the DAMTP Statistical Physics and Soft Matter Seminar series. This talk is included in these lists:
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