Algorithms Inspired by Petri Nets in Modeling of Complex Biological Systems
Anna Gogolińska · 2015
Biological system may be a population, an organism, a physiological system, a tissue, a cell or even a biomolecule such as a protein or a piece of nucleic acid. Biological sciences have made tremendous progress in recent years, however, many crucial phenomena are still poorly understood and they need strong efforts in all fields, including computer science. Mathematical models of the complex systems should grasp their main features from the physical reality and transfer them into mathematical entities. Many modeling methods have been proposed over the last years, like for example ordinary differential equations (ODEs), process calculi, Boolean networks, Bayesian networks, stochastic equations, or cellular automata. One of the mathematical modeling techniques, used in this thesis, are Petri nets (PNs).