기초과학연구원 의생명수학그룹
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We will discuss about "Model Reduction for the Chemical Master Equation: an Information-Theoretic Approach", Öcal, Kaan, Guido Sanguinetti, and Ramon Grima., arXiv preprint arXiv:2210.05329 (2022). Abstract: The complexity of mathematical models in biology has rendered model reduction an essential tool in the quantitative biologist's toolkit. For stochastic reaction networks described using the Chemical Master Equation, commonly … |
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Shift workers experience profound circadian disruption due to the nature of their work, which often has them working at times when their internal clock is sending a strong signal for sleep. Mathematical models can be used to generate recommendations for shift workers that shift their body's clock to better align with their work schedules, to … |
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Wearable analytics hold far more potential than sleep tracking or step counting. In recent years, a number of applications have emerged which leverage the massive quantities of data being amassed by wearables around the world, such as real-time mood detection, advanced COVID screening, and heart rate variability analysis. Yet packaging insights from research for success …
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Cells make individual fate decisions through linear and nonlinear regulation of gene network, generating diverse dynamics from a single reaction pathway. In this colloquium, I will present two topics of our recent work on signaling dynamics at cellular and patient levels. The first example is about the initial value of the model, as a mechanism … |
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We will discuss about “PI-VAE: Physics-Informed Variational Auto-Encoder for stochastic differential equations”, Zhong, Weiheng, and Hadi Meidani, Computer Methods in Applied Mechanics and Engineering 403 (2023): 115664. Abstract We propose a new class of physics-informed neural networks, called the Physics-Informed Variational Auto-Encoder (PI-VAE), to solve stochastic differential equations (SDEs) or inverse problems involving SDEs. In … |
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The circadian clock orchestrates a vast array of behavioral and physiological processes with a 24-hour cycle, enabling nearly all organisms -- from bread mold to fruit-flies to humans -- to anticipate and adapt to the Earth's day. Entrainable by environmental cue, the rhythm itself is generated by a self-sustained molecular oscillator present in nearly every …
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We will discuss about “Detecting critical state before phase transition of complex biological systems by hidden Markov model”, Chen, Pei, et al. Bioinformatics 32.14 (2016): 2143-2150. Abstract Motivation: Identifying the critical state or pre-transition state just before the occurrence of a phase transition is a challenging task, because the state of the system may … |
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Transmission of SARS-CoV-2 relies on interactions between humans. Heterogeneity and stochasticity both in human-human interactions and in the transmission of the virus give rise to non-linear infection networks that gain complexity with time. We assessed the limits of control and the effect of pharmaceutical and non-pharmaceutical measures against COVID‐19 outbreaks with a detailed community‐specific agent-based model … |
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Abstract: Circadian clocks control the timing and 24-hour periodicity of virtually all physiological rhythms including sleep, cognition, and metabolism. There are optimal times for most behaviours; e.g., the best sleep is achieved during low circadian activity (night), while meals and physical exercise are best placed during high circadian activity (day) when metabolic rates, stress hormone … |
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Abstract: The ability to reliably engineer the mammalian cell will impact a variety of applications in a disruptive way, including cell fate control and reprogramming, targeted drug delivery, and regenerative medicine. However, our current ability to engineer mammalian genetic circuits that behave as predicted remains limited. These circuits depend on the intra and extra cellular …
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We will discuss about “Multiparameter persistent homology landscapes identify immune cell spatial patterns in tumors”, Vipond, Oliver, et al, Proceedings of the National Academy of Sciences 118.41 (2021): e2102166118. Abstract Highly resolved spatial data of complex systems encode rich and nonlinear information. Quantification of heterogeneous and noisy data—often with outliers, artifacts, and mislabeled points—such as … |
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