Deciphering circadian clock cell network morphology within the biological master clock, the suprachiasmatic nucleus

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

Abstract: The biological master clock, the suprachiasmatic nucleus (SCN) of a mouse, contains many (~20,000) clock cells heterogeneous, particularly with respect to their circadian period. Despite the inhomogeneity, within an intact SCN, they maintain a very high degree of circadian phase coherence, which is generally rendered visible as system-wide propagating phase waves. The phase coherence

Statistical Inference with Neural Network Imputation for Item Nonresponse

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

Abstract: We consider the problem of nonparametric imputation using neural network models. Neural network models can capture complex nonlinear trends and interaction effects, making it a powerful tool for predicting missing values under minimum assumptions on the missingness mechanism. Statistical inference with neural network imputation, including variance estimation, is challenging because the basis for function

Collective Oscillations in coupled cell systems

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

We will discuss about "Collective Oscillations in coupled cell systems", Chen and Sinh, Bulletin of Mathematical Biology, 2021 We investigate oscillations in coupled systems. The methodology is based on the Hopf bifurcation theorem and a condition extended from the Routh–Hurwitz criterion. Such a condition leads to locating the bifurcation values of the parameters. With such

DeepCME: A deep learning framework for solving the Chemical Master Equation

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

We will discuss about “DeepCME: A deep learning framework for solving the Chemical Master Equation,” Gupta et al., bioRxiv, 2021 Stochastic models of biomolecular reaction networks are commonly employed in systems and synthetic biology to study the effects of stochastic fluctuations emanating from reactions involving species with low copy-numbers. For such models, the Kolmogorov’s forward

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Inference for Circadian Pacemaking

ZOOM ID: 709 120 4849 (ibsbimag)

This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) Abstract: Organisms have evolved an internal biological clock which allows them to temporally regulate and organize their physiological and behavioral responses to cope in an optimal way with the fundamentally periodic nature of the environment. It is now well established that the

Modeling Cell-to-Cell Communication Networks Using Response-Time Distributions

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

We will discuss about “Modeling Cell-to-Cell Communication Networks Using Response-Time Distributions”, Thurley et al., Cell Systems, 2021 Abstract: Cell-to-cell communication networks have critical roles in coordinating diverse organismal processes, such as tissue development or immune cell response. However, compared with intracellular signal transduction networks, the function and engineering principles of cell-to-cell communication networks are far

Parameter Estimation in a Model of the Human Circadian Pacemaker Using a Particle Filter

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

We will discuss about “Parameter Estimation in a Model of the Human Circadian Pacemaker Using a Particle Filter”, Bonarius et. al., IEEE Trans. Biomed. Eng., 2021 Abstract Objective: In the near future, real-time estimation of peoples unique, precise circadian clock state has the potential to improve the efficacy of medical treatments and improve human performance

Inference method for a stochastic target-mediated drug disposition model via ABC-MCMC

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

Abstract: Inference method for a stochastic target-mediated drug disposition model via ABC-MCMC In this study, we discuss model robustness. Model robustness is consistent performance over variations of parameters. We formulate a stochastic target-mediated drug (TMDD) model, one of the pharmacokinetic models, to capture bi-exponential drug decay in plasma. A stochastic process is used to account

Scalable Modeling Approaches in Systems Immunology

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

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 molecular and cellular players. Thus, mechanistic, predictive models describing such systems need to address this multiscale nature. A general outstanding problem is to cope with

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