A state-of-the-art problem in Computational Systems Biology is to provide suitable tools to model and predict the behaviour of multicellular systems (tissues, embryos) where biological interactions occur both inside and between cells (or compartments in general). Starting from existing computational models and languages such as stochastic π-calculus, Petri Nets, mobile ambients, and membrane computing, we developed a new computational framework based on (i) a compositional model for biological compartments, and (ii) an enhanced model of chemical rules addressing also biomechanical actions such as substances diffusion across membranes or compartments splitting. We tested a fragment of the framework using a case study based on spatial pattern formation in embryogenesis, where the interplay between cells' internal dynamics and cell-to-cell interactions has a central role.
['Sara Montagna', 'Mirko Viroli']
A computational framework for modelling multicellular biochemistry