Stochastic reaction networks in dynamic compartment populations

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

We will discuss about “Stochastic reaction networks in dynamic compartment populations”, Duso and Zechner, PNAS, 2020 Abstract: Compartmentalization of biochemical processes underlies all biological systems, from the organelle to the

Cellular signaling beyond the Wiener-Kolmogorov limit

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

We will discuss about "Cellular signaling beyond the Wiener-Kolmogorov limit", Weisenberger et al., bioRxiv, 2021 Abstract: Accurate propagation of signals through stochastic biochemical networks involves significant expenditure of cellular resources.

Machine learning of stochastic gene network phenotypes

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

We will discuss about "Machine learning of stochastic gene network phenotypes", Park et al., bioRxiv, 2019 Abstract: A recurrent challenge in biology is the development of predictive quantitative models because

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

IBS 의생명수학그룹 Biomedical Mathematics Group
기초과학연구원 수리및계산과학연구단 의생명수학그룹
대전 유성구 엑스포로 55 (우) 34126
IBS Biomedical Mathematics Group (BIMAG)
Institute for Basic Science (IBS)
55 Expo-ro Yuseong-gu Daejeon 34126 South Korea
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