日時：	2026年9月14日（月）13：30～15：00
場所：	医生物学研究所　医生研３号館3階セミナー室（312室） Seminar Room (312), 3rd floor, Bldg. #3 Institute for Life and Medical Sciences, Kyoto University
演者：	Konstantin Mischaikov Department of Mathematics, Rutgers University, USA
演題：	Dynamics of Regulatory Networks（講演言語：英語／Language: English）

講演要旨

ynamics is parameter dependent. Thus, dynamics cannot be determined
directly from a regulatory network diagram that purports to identify
how genes/proteins/biochemical units interact; an additional level of
modeling is required. Two popular choices are Boolean models and
Ordinary Differential Equations (ODEs). The advantage of Boolean
models is that they are easy to compute and reduce the need for
parameter identification. The disadvantage is that the resulting
dynamics is highly simplified, potentially misleading, and difficult
to associate with parameters. The advantage of ODEs is that they
provide precision, but at high experimental cost (nonlinearities and
parameters need to be identified) and at high computational cost
(solving the ODE over multiple initial conditions).

In this talk I will discuss a third approach: Dynamic Signatures
Generated by Regulatory Networks (DSGRN). It is based on
characterizing dynamics via order theory and algebraic topology. The
major points I wish to convey about this novel approach to dynamics
are the following:
1. The regulatory network defines a finite combinatorial
parameterization of the DSGRN dynamics.
2. DSGRN dynamics is efficiently computable and can be used to readily
detect not only dynamics, but also global bifurcations of biological
interest.
3. DSGRN dynamics can be identified with dynamics of Ordinary
Differential Equations.
4. Boolean dynamics is a subset of DSGRN dynamics and this DSGRN
dynamics provides a natural parameterization for the analysis of
Boolean networks.
5. DSGRN dynamics can be readily compared against data.

Theoretical Biology Seminar（Konstantin Mischaikov氏_Rutgers University）

contact: Atsushi Mochizuki
　　　　　Laboratory of Mathematical Biology,
　　　　　Institute for Life and Medical Sciences, Kyoto University
Email: mochi[@]infront.kyoto-u.ac.jp
Tel: 075-751-4612