Dr. Reka Albert, Pennsylvania State University

Abstract: Cell types and cellular behaviors can be abstracted as attractors of a dynamic system of interacting molecules. My group collaborates with wet-bench biologists to develop and validate Boolean models of specific systems. We use these models to predict interventions that drive the system into desired attractors and away from undesired ones. Several such predictions were validated by our collaborators.  This talk will present two general topics that arose from the specific models.
The first 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 any system into a desired attractor. We have translated the concept of stable motif to multi-level and ODE models.

The second is our development of a genetic algorithm-based workflow for automated evaluation and refinement of Boolean models. This implementation applies to any biological system for which an interaction network exists and enough perturbation experiments have been done. The genetic algorithm adjusts the functions of the model to enhance agreement with a corpus of curated experimental results. We leverage existing mechanistic knowledge to automatically limit the search space to biologically plausible models. To account for the interdependence of experiment results, we develop a hierarchical scoring technique for assessing model performance. We demonstrate the effectiveness of the workflow by significantly improving a Boolean model previously developed by our group. The principles of our workflow apply to multi-level models.

We expect that decreasing the effort necessary to formulate validated network-based models will increase the applications of stable motif-based attractor control, forming the foundation of therapeutic strategies on a wide application domain.

Bio: Prof. Réka Albert received her Ph.D. in Physics from the University of Notre Dame, working with Prof. Albert-László Barabási, then did postdoctoral research in mathematical biology at the University of Minnesota, working with Prof. Hans G. Othmer. She joined Penn State in 2003, where she currently is a Distinguished Professor of Physics with adjunct appointments in the Department of Biology and the Huck Institute of the Life Sciences. Prof. Albert is a theoretical/computational scientist who works on predictive modeling of biological regulatory networks at multiple levels of organization. She is a fellow of the American Physical Society, the Network Science Society, and the American Association for the Advancement of Science. She is also an external member of the Hungarian Academy of Sciences. She was a recipient of an NSF Career Award (2007), the Maria Goeppert-Mayer Award (2011), and the Distinguished Graduate Alumna Award of the University of Notre Dame (2016).

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Meeting ID: 998 2458 4542

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