Ewerton Rocha Vieira, Rutgers University

Abstract

Many time varying systems in science are traditionally modeled by ordinary differential equations (ODE). However, for multi-scale systems, where the variables and parameters are typically numerous and poorly measured, it is extremely challenging to perform a direct analysis to understand the global dynamics (attractors, oscillations and other complex dynamics).

To address this challenge, we have developed coarser modeling tools based on combinatorics and algebraic topology. In this novel approach, we move away from the classical ODE analysis (trajectories and invariant sets) and focus toward a robust, scalable and computable description of dynamics in terms of annotated graphs. In particular, for gene regulatory networks, we have developed a software tool Dynamic Signatures Generated by Regulatory Networks (DSGRN) that can take as input a regulatory network and output a database that describes the global dynamics over a large high dimensional parameter space. After introducing the main ideas, I will show some examples where DSGRN can quickly analyze the network of interest and address the presence of oscillations and feedback loops.

Bio:

Ewerton Rocha Vieira is a postdoctoral researcher at DIMACS associated with the DATA-INSPIRE Institute. His research interests are focused on the use of topology, algebraic topology and dynamical systems to understand and obtain information from time varying systems (flows, differential equations and continuous maps).   He received his Ph.D. in Mathematics from ‎University of Campinas in São Paulo - Brazil under the supervision of Ketty Abaroa de Rezende with one year Ph.D. internship at Northwestern University under the supervision of John Franks. He had visiting positions at University of Maine, University of Brasília, and Rutgers University. Currently, he is also a tenured adjunct professor on a leave of absence at Federal University of Goiás (Brazil). 

SPECIAL NOTE: This seminar is presented online only.

You can join via  Webex

Meeting number (access code):  138 325 2462 

Meeting password: 1234

Presented in association with the DATA-INSPIRE TRIPODS Institute.