Scalable Modeling Approaches in Systems Immunology

B305 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

Abstract: Systems biology seeks to build quantitative predictive models of biological system behavior. Biological systems, such as the mammalian immune system, operate across multiple spatiotemporal scales with a myriad of

COVID19 – Mathematical Modeling and Machine Learning

B305 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

Abstract This presentation include the following two topics. First of all, we consider a spread model of COVID-19 with time-dependent parameters via deep learning. We developed a SIR model with

Methods for characterizing circadian physiology from wearables

B378 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

Abstract Non-invasive data collection in real-world settings with wearables provides a new opportunity for characterizing daily physiology. However, accurate and efficient characterization remains an open problem because the complex autoregressive

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IBS Biomedical Mathematics Group (BIMAG)
Institute for Basic Science (IBS)
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