Zobrazeno 1 - 10
of 240
pro vyhledávání: '"Kobayashi, Tetsuya J."'
Controlling the stochastic dynamics of biological populations is a challenge that arises across various biological contexts. However, these dynamics are inherently nonlinear and involve a discrete state space, i.e., the number of molecules, cells, or
Externí odkaz:
http://arxiv.org/abs/2409.17488
Despite being optimized, the information processing of biological organisms exhibits significant variability in its complexity and capability. One potential source of this diversity is the limitation of resources required for information processing.
Externí odkaz:
http://arxiv.org/abs/2409.14003
Biological information processing manifests a huge variety in its complexity and capability among different organisms, which presumably stems from the evolutionary optimization under limited computational resources. Starting from the simplest memory-
Externí odkaz:
http://arxiv.org/abs/2409.14002
Autor:
Nakashima, So, Kobayashi, Tetsuya J.
Reinforcement Learning (RL) offers a fundamental framework for discovering optimal action strategies through interactions within unknown environments. Recent advancement have shown that the performance and applicability of RL can significantly be enh
Externí odkaz:
http://arxiv.org/abs/2408.09493
Autor:
Kato, Masaki, Kobayashi, Tetsuya J.
Collective migration is a phenomenon observed in various biological systems, where the cooperation of multiple cells leads to complex functions beyond individual capabilities, such as in immunity and development. A distinctive example is cell populat
Externí odkaz:
http://arxiv.org/abs/2407.15298
Analyzing the motion of multiple biological agents, be it cells or individual animals, is pivotal for the understanding of complex collective behaviors. With the advent of advanced microscopy, detailed images of complex tissue formations involving mu
Externí odkaz:
http://arxiv.org/abs/2405.16503
Autor:
Nakamura, Kento, Kobayashi, Tetsuya J.
Eukaryotic cells perform chemotaxis by determining the direction of chemical gradients based on stochastic sensing of concentrations at the cell surface. To examine the efficiency of this process, previous studies have investigated the limit of estim
Externí odkaz:
http://arxiv.org/abs/2405.04810
Chemical reaction networks (CRNs) exhibit complex dynamics governed by their underlying network structure. In this paper, we propose a novel approach to study the dynamics of CRNs by representing them on species graphs (S-graphs). By scaling concentr
Externí odkaz:
http://arxiv.org/abs/2404.14336
Understanding deaths and life-death boundaries of cells is a fundamental challenge in biological sciences. In this study, we present a theoretical framework for investigating cell death. We conceptualize cell death as a controllability problem within
Externí odkaz:
http://arxiv.org/abs/2403.02169
We delve into growing open chemical reaction systems (CRSs) characterized by autocatalytic reactions within a variable volume, which changes in response to these reactions. Understanding the thermodynamics of such systems is crucial for comprehending
Externí odkaz:
http://arxiv.org/abs/2312.14435