Speaker
Description
Simulations are often used to analyse and dissect complex experimental systems where cells modify their behaviour while moving, growing and adapting to internal and external stimuli. A number of procedures and tools have been proposed aimed to model cell behaviour, ranging from whole cell mass simulation to lattice based models, where cells are represented by one or more lattice elements. More recently, simulation systems have been shifting towards models based on individual cell agents where mass, volume and morphology behave according to more or less precise rules and models. Here we present an agent-based simulation system, SimulCell, where individual cells are simulated by using models of cellular processes, such as growth, proliferation and migration, to create synthetic populations which resemble experimental ones. We initially built on a novel motion model, able to describe movement in experimental cell populations using a combination of random, persistence and bias components. The model was extended by adding cell-cell repulsion, movement modifications due to attachment state and mitosis and cell ability to chose a direction by reacting to a field such as that produced by an attractant, among other changes. Within the simulator, in addition to movement features, each cell is also able to individually control its volumetric growth, survival and replication as well as cell cycle transitions following volume changes and external stimuli such as local cell confluence or the presence of growth factors or other drugs in the medium. Support for interactions between cells and their environment was introduced to react to changes in medium composition and other events, such as physical damage or chemical modifications occurring in the culture plate. Integrating all these models and features in SimulCell, and using parameters taken from experimental cell populations, the simulation produces cells that grow, move and undergo cell division modulating their behaviour according to their current state and the surrounding environment. Stochastic changes and combination of many individual cells result in populations which introduce variability in response to different stimuli while preserving the specific features of the original experimental cell population.
| Department | Ceinge - Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II |
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