LUNCH COMPLEJO VIRTUAL
CONSORCIO DE UNIVERSIDADES POR LA CIENCIA
Network-based dynamic modeling of biological systems: toward understanding and control
Réka Albert
Pennsylvania State University
Centro de Ciencias de la Complejidad (C3), UNAM
28 de enero de 2021, 13 horas
Informes: disenio@c3.unam.mx
Abstract:
My group is using network science and dynamic modeling to understand the emergent properties of biological systems. As an example, we think of cell types as attractors of a dynamic system of interacting (macro)molecules, and we aim to find the network patterns that determine these attractors. We collaborate with wet-bench biologists to develop and validate predictive dynamic models of specific systems. Over the years we found that network-based discrete dynamic modeling is very useful in synthesizing causal interaction information into a predictive, mechanistic model. We use the accumulated knowledge gained from specific models to draw general conclusions that connect a network's structure and dynamics. An example of such a general connection is our identification of stable motifs, which are self-sustaining cyclic structures that determine points of no return in the dynamics of the system. We have shown that control of stable motifs can guide the system into a desired attractor. We have recently translated the concept of stable motif to a broad class of continuous (ODE-based) models. Stable motif - based attractor control can form the foundation of therapeutic strategies on a wide application domain.
Representative references:
- JGT Zañudo, SN Steinway, R Albert, Discrete dynamic network modeling of oncogenic signaling: Mechanistic insights for personalized treatment of cancer, Current Opinion in Systems Biology 9, 1-10 (2018).
- JC Rozum, R Albert, Identifying (un)controllable dynamical behavior in complex networks, PLOS Computational Biology 14, e1006630 (2018).