Abstract
This paper discusses the design goals and the first developments of Proto-Plasm, a novel computational environment to produce libraries of executable, combinable and customizable computer models of natural and synthetic biosystems, aiming to provide a supporting framework for predictive understanding of structure and behaviour through multiscale geometric modelling and multiphysics simulations. Admittedly, the Proto-Plasm platform is still in its infancy. Its computational framework—language, model library, integrated development environment and parallel engine—intends to provide patient-specific computational modelling and simulation of organs and biosystem, exploiting novel functionalities resulting from the symbolic combination of parametrized models of parts at various scales. Proto-Plasm may define the model equations, but it is currently focused on the symbolic description of model geometry and on the parallel support of simulations. Conversely, CellML and SBML could be viewed as defining the behavioural functions (the model equations) to be used within a Proto-Plasm program. Here we exemplify the basic functionalities of Proto-Plasm, by constructing a schematic heart model. We also discuss multiscale issues with reference to the geometric and physical modelling of neuromuscular junctions.
Highlights
The physiome of an individual or a species is the description of its functional behaviour
The Physiome Project (Higgins et al 2001) was the first worldwide effort to provide a computational framework for understanding human physiology
It is largely recognized that evolving physiome activities will increasingly influence medicine and biomedical research, with an ever increasing demand for specific and robust computational platforms
Summary
The physiome of an individual or a species is the description of its functional behaviour. Our vision is that description languages are not sufficient, and that totally new progressive and adaptive methods for terascale geometric modelling are needed, combined with novel adaptive methods for multiphysics and multiscale simulation, working on parallel and distributed supercomputers Both symbolic and hierarchical characterizations of the various components should be allowed for, as well as shape reconstruction from high-resolution nuclear magnetic resonance (NMR) and other volume imaging techniques. An algorithm for parallel, progressive Boolean operations is given in Paoluzzi et al (2004); several graphics and modelling techniques are integrated into the same format in Scorzelli et al (in press) Another significant difference between our approach and more conventional ones is that we focus on solid mesh decomposition, instead of boundary representation.
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