기초과학연구원 의생명수학그룹
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We will discuss about "The 103,200-arm acceleration dataset in the UK Biobank revealed a landscape of human sleep phenotypes", Katori et al., PNAS, 2022. Abstract: Human sleep phenotypes can be defined and diversified by both genetic and environmental factors. However, some sleep phenotypes are difficult to evaluate without long-term, precise sleep monitoring, for which simple … |
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This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) Abstract: The idea of balance between excitation and inhibition is central in the theory of biological neural networks. I will give a brief introduction to the concept of such balance, and an overview of the mathematical ideas that can be used to study …
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This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) Abstract: I will first describe how to extend the theory of balanced networks to account for synaptic plasticity. This theory can be used to show when a plastic network will maintain balance, and when it will be driven into an unbalanced state. …
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We will discuss about "Optimizing Oscillators for Specific Tasks Predicts Preferred Biochemical Implementations", Agrahar and Rust., bioRxiv, 2022. Abstract: Oscillatory processes are used throughout cell biology to control time-varying physiology including the cell cycle, circadian rhythms, and developmental patterning. It has long been understood that free-running oscillations require feedback loops where the activity of one … |
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This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) Abstract: I will introduce mathematical and computational methods for spatio-temporal modelling in molecular and cell biology, including all-atom and coarse-grained molecular dynamics (MD), Brownian dynamics (BD), stochastic reaction-diffusion models and macroscopic mean-field equations. Microscopic (BD, MD) models are based on the simulation …
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This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) Abstract: I will discuss the development, analysis and applications of multi-resolution methods for spatio-temporal modelling of intracellular processes, which use (detailed) Brownian dynamics or molecular dynamics simulations in localized regions of particular interest (in which accuracy and microscopic details are important) and … |
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This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) Abstract: Quantitative characterization of biomolecular networks is important for the analysis and design of network functionality. Reliable models of such networks need to account for intrinsic and extrinsic noise present in the cellular environment. Stochastic kinetic models provide a principled framework for … |
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Abstract. Matrix/tensor factorization models such as principal component analysis , nonnegative matrix factorization, and CANDECOM/PARAFAC tensor decomposition provide powerful framework for dimension reduction and interpretable feature extraction, which are important in analyzing high-dimensional data that comes in large volume. Their diverse applications include image denoising and reconstruction, dictionary learning, topic modeling, and network data analysis. … |
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We will discuss about "Approximating Solutions of the Chemical Master Equation using Neural Networks", Sukys et al., bioRxiv, 2022 Abstract: The Chemical Master Equation (CME) provides an accurate description of stochastic biochemical reaction networks in well-mixed conditions, but it cannot be solved analytically for most systems of practical interest. While Monte Carlo methods provide a … |
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