Network-based modeling of cell fates, and its use in targeted therapies

Réka Albert

Time: 8:20 - 9:10 AM

Type: Invited presentation

Affiliation: The Huck Institutes of the Life Sciences, Center for Infectious Disease Dynamics,
Pennsylvania State University

Abstract

Cell types or cell fates can be considered as attractors of a genome-scale intracellular regulatory network. A practical and effective method of modeling the dynamics of this network is by discrete dynamic (logic) models. These models can be built from qualitative or relative information and have a sufficient dynamical richness to capture the essential characteristics of cellular attractors. This talk will use a model of T cell signaling in the context of the disease T-LGL leukemia to illustrate how a logic model captures the two observed outcomes and can predict interventions to eliminate the disease outcome. I will also present recently proposed methods to integrate network structure and logic which empower predictive network analysis. For example, this analysis can be used to predict interventions that guide the system toward a desired attractor or away from an undesired one, regardless of the current state of the system.