The University of Tokyo · Computer Science
Professor Kazuyuki Aihara's research lab specializes in computational systems biology and nonlinear dynamics, focusing on modeling and analyzing complex biological signaling networks using mathematical and computational approaches. The lab integrates high-throughput 'omics' data with advanced optimization techniques, such as integer and linear programming, to reconstruct signal transduction networks and understand cellular decision-making processes. A key research direction involves the study of hybrid dynamical systems, particularly those combining continuous biochemical reactions with discrete regulatory events like gene switching or protein activation. The lab also explores the theoretical foundations of nonlinear dynamics in biological and engineered systems, aiming to uncover universal principles in systems biology and control theory.
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Signal transduction is an important process that transmits signals from the outside of a cell to the inside to mediate sophisticated biological responses. Effective computational models to unravel such a process by taking advantage of high-throughput genomic and proteomic data are needed to understand the essential mechanisms underlying the signaling pathways. In this article, we propose a novel method for uncovering signal transduction networks (STNs) by integrating protein interaction with gen
In this introductory article, we survey the contents of this Theme Issue. This Theme Issue deals with a fertile region of hybrid dynamical systems that are characterized by the coexistence of continuous and discrete dynamics. It is now well known that there exist many hybrid dynamical systems with discontinuities such as impact, switching, friction and sliding. The first aim of this Issue is to discuss recent developments in understanding nonlinear dynamics of hybrid dynamical systems in the two
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