Community detection by graph Voronoi diagrams

Intractable diseases such as cancer are associated with breakdown in multiple individual functions, which conspire to create unhealthy phenotype-combinations. An important challenge is to decipher how these functions are coordinated in health and disease. We approach this by drawing on dynamical systems theory. We posit that distinct phenotype-combinations are generated by interactions among robust regulatory switches, each in control of a discrete set of phenotypic outcomes. First, we demonstrate the advantage of characterizing multi-switch regulatory systems in terms of their constituent switches by building a multiswitch cell cycle model which points to novel, testable interactions critical for early G2/M commitment to division. Second, we define quantitative measures of dynamical modularity, namely that global cell states are discrete combinations of switch-level phenotypes. Finally, we formulate three general principles that govern the way coupled switches coordinate their function.

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Recommended citation:Deritei, D., Lazar, Z.I., Papp, I., Jarai-Szabo, F., Sumi, R., Varga, L., Regan, E.R. and Ercsey-Ravasz, M., 2014. Community detection by graph Voronoi diagrams. New Journal of Physics, 16(6), p.063007.