Emergence of Novel Functional Assembly by Evo-Physico Information Coupling

Researchers from #UTokyo_IIS have found that single cells in collective chemotaxis act like agents in distributed reinforcement learning, utilizing the environment as an “external memory” and exhibiti...

An optimal estimation and control framework is proposed that explicitly accounts for biological resource limitations. Application of this framework to biological information processing shows that reso...

Chemical reaction network (CRN) theory is widely utilized to model and analyze a wide range of biochemical phenomena. Structural transformations and reductions serve as essential tools to better under...

Summary: Phycocyanobilin-bound miRFP670 is bright and photostable, enabling quantitative fluorescent cross-correlation spectroscopy analysis of cyclin–CDK interactions in living fission yeast and mamm...

While it is well established that self-propelled particles with alignment interactions can exhibit orientational order, the impact of self-replication and annihilation, which are key characteristics in cellular systems, on spatiotemporal order remains poorly understood. To explore the interplay between self-propulsion and self-replication, we introduce the active Brownian bug model, in which self-propelled agents undergo stochastic, density-dependent replication and constant-rate death. Despite the absence of alignment interactions, the system exhibits flocking behavior characterized by high orientational order, while maintaining ordered hexagonal arrays. This emergent order arises from stochastic birth and death processes, offering a mechanism for flocking in proliferating cellular populations.

In open nonequilibrium systems, interactions that break the action-reaction symmetry are ubiquitous in nature. While such nonreciprocal interactions have been implemented for quantum systems, they typically require fine microscopic control of dissipation. Here, Hanai, Ootsuki and Tazai propose a dissipation engineering scheme that induces nonreciprocal interactions in solid state materials, giving rise to a persistent many-body chase-and-runaway dynamics of magnetism in layered ferromagnets.

Researchers from #UTokyo_IIS have formulated a mathematical theory for dynamical networks made of biological agents, such as humans