ABSTRACT / In this talk I'm going to briefly introduce Boolean networks and systems biology in general - while establishing the motivation for our work. In this wider picture I'm going to present the body of work that will constitute my upcoming thesis, and how it fits into this growing discipline. My main focus is two-fold: it has an empirical side where we introduce and study Boolean regulatory models for the cell cycle - the process that coordinates the division of cells, the most fundamental process of life as we know it. The other side of my work is more theoretical and it focuses on understanding (in network terms) how the hierarchy of decision making modules coordinates and gives rise to complex processes that ensure that biological systems are both adaptive and robust. We call this framework dynamical modularity, which, beside its conceptual importance, is also a useful tool in reducing the vast state-space of regulatory networks - which, in turn, allows for more efficient ways to produce predictions useful in medicine and drug development.
BIO / Dávid studies the complex regulatory networks governing living cells. His main inquiries include the identification of stable motifs and their ability to control both empirical and synthetic regulatory networks, the effects of different types of noise on regulatory systems and their stability, as well as the hierarchical organization of the decision making processes, more specifically, how very complicated interactions can be responsible for simple, discrete decisions on multiple levels. Dávid is a physicist by training and has had previous collaborations with Babes Bolyai University, Beth Israel Deaconess Medical Center - Harvard Medical School, University of Notre Dame and the College of Wooster.