기초과학연구원 의생명수학그룹
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High accuracy of major biological processes relies on the ability of the participating enzymatic molecules to preferentially select the correct substrate from a pool of chemically similar substrates by activating the so-called proofreading mechanisms. While the importance of such mechanisms is widely accepted, it is still unclear how evolution has optimized biological systems with respect … |
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Collective cell movement is critical to the emergent properties of many multicellular systems including microbial self-organization in biofilms, wound healing, and cancer metastasis. However, even the best-studied systems lack a complete picture of how diverse physical and chemical cues act upon individual cells to ensure coordinated multicellular behavior. Myxococcus xanthus is a model bacteria famous … |
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We introduce a sufficient graphical model by applying the recently developed nonlinear sufficient dimension reduction techniques to the evaluation of conditional independence. The graphical model is nonparametric in nature, as it does not make distributional assumptions such as the Gaussian or copula Gaussian assumptions. However, unlike a fully nonparametric graphical model, which relies on the … |
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We will discuss about “Inference and uncertainty quantification of stochastic gene expression via synthetic models”, Öcal et al., J. R. Soc. Interface. Abstract Estimating uncertainty in model predictions is a central task in quantitativebiology. Biological models at the single-cell level are intrinsically stochastic and nonlinear, creating formidable challenges for their statistical estimation which inevitably has … |
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We will discuss about “A multi-scale model explains oscillatory slowing and neuronal hyperactivity in Alzheimer’s disease”, Alexandersen, Christoffer G., et al., Journal of the Royal Society Interface 20.198 (2023): 20220607. Abstract Alzheimer’s disease is the most common cause of dementia and is linked to the spreading of pathological amyloid-β and tau proteins throughout the brain. Recent studies … |
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Abstract: Stochasticity in gene expression is an important source of cell-to-cell variability (or noise) in clonal cell populations. So far, this phenomenon has been studied using the Gillespie Algorithm, or the Chemical Master Equation, which implicitly assumes that cells are independent and do neither grow nor divide. This talk will discuss recent developments in modelling … |
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We propose a kernel-based estimator to predict the mean response trajectory for sparse and irregularly measured longitudinal data. The kernel estimator is constructed by imposing weights based on the subject-wise similarity on L2 metric space between predictor trajectories, where we assume that an analogous fashion in predictor trajectories over time would result in a similar … |
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We will discuss about “Parameter Estimation of Power Electronic Converters With Physics-Informed Machine Learning”, Zhao, Shuai, et al., IEEE Transactions on Power Electronics 37.10 (2022): 11567-11578. Abstract Physics-informed machine learning (PIML) has been emerging as a promising tool for applications with domain knowledge and physical models. To uncover its potentials in power electronics, this article … |
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Dongju Lim: Mood Prediction for Bipolar Disorder Patient with Sleep Pattern Information Eui Min Jeong:Noise attenuation through the multiple repression mechanism in transcription Hyeontae Jo: Parameter estimation with discontinuously switching system |
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We will discuss about “Uncovering specific mechanisms across cell types in dynamical models”, Hauber, Adrian Lukas, Marcus Rosenblatt, and Jens Timmer., bioRxiv (2023): 2023-01. Abstract Ordinary differential equations are frequently employed for mathematical modeling of biological systems. The identification of mechanisms that are specific to certain cell types is crucial for building useful models and to … |
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