: 8:20 - 9:10 AM
Type: Invited presentation
Affiliation: The Huck Institutes of the Life Sciences, Center for Infectious Disease Dynamics,
Pennsylvania State University
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.