Biomedical Mathematics Seminar

Events

Events Search and Views Navigation

Event Views Navigation

Today

  • What is the role of oscillatory signals in intracellular systems?

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

    Oscillatory signals are ubiquitously observed in many different intracellular systems such as immune systems and DNA repair processes. While we know how oscillatory signals are created, we do not fully understand what a critical role they play to regulate signal pathway systems in cells. Recently by using a stochastic nucleosome system, we found that a …

    Continue Reading

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

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

    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 …

    Continue Reading

  • Statistical Inference with Neural Network Imputation for Item Nonresponse

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

    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 …

    Continue Reading

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

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

    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 …

    Continue Reading

  • 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 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 …

    Continue Reading

  • Bayesian model calibration and sensitivity analysis for oscillating biochemical experiments

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

    Abstract: Most organisms exhibit various endogenous oscillating behaviors, which provides crucial information about how the internal biochemical processes are connected and regulated. Along with physical experiments, studying such periodicity of organisms often utilizes computer experiments relying on ordinary differential equations (ODE) because configuring the internal processes is difficult. Simultaneously utilizing both experiments, however, poses a …

    Continue Reading

  • 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 time-dependent parameters via deep learning methods. Furthermore, we validated the model with the conventional model to confirm its convergent nature. Next, We also developed a …

    Continue Reading

  • The Graph convolutional Networks (GCN) with Persistent Homology and its application 1/4

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

    (1) GCN and its Application. We introduce the GCN by reviewing the monumental paper " Semi-Supervised Classification with the Graph Convolutional Networks", ICLR 2018 by Kipf and Welling. We are going to much detail the algorithm of message aggregation and passings and learning processes. Code ; https://github.com/tkipf/gcn (2) Graph Attention networks(GAT) and its Applications. Bengio …

    Continue Reading