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 organisation of the decision making processes, more specifically, how can very complicated interactions be responsible for simple, discrete decisions on multiple levels.
Dávid is a physicist by training and had previous collaborations with Babes Bolyai University, Beth Israel Deaconess Medical Center - Harvard Medical School, University of Notre Dame and the College of Wooster.
Deritei, Dávid, et al. "Community detection by graph Voronoi diagrams." New Journal of Physics 16.6 (2014): 063007.
Deritei, Dávid, et al. "Principles of dynamical modularity in biological regulatory networks." Scientific reports 6 (2016).
Lázár, Z. I., Papp, I., Varga, L., Járai-Szabó, F., Deritei, D., & Ercsey-Ravasz, M. (2017). Stochastic graph Voronoi tessellation reveals community structure. Physical Review E, 95(2), 022306.
Sizek, Herbert, Andrew Hamel, Dávid Deritei, Sarah Campbell, and Erzsébet Ravasz Regan. "Boolean model of growth signaling, cell cycle and apoptosis predicts the molecular mechanism of aberrant cell cycle progression driven by hyperactive PI3K." PLoS computational biology 15, no. 3 (2019): e1006402.