2,155 research outputs found
Aspects of multiscale modelling in a process algebra for biological systems
We propose a variant of the CCS process algebra with new features aiming at allowing multiscale modelling of biological systems. In the usual semantics of process algebras for modelling biological systems actions are instantaneous. When different scale levels of biological systems are considered in a single model, one should take into account that actions at a level may take much more time than actions at a lower level. Moreover, it might happen that while a component is involved in one long lasting high level action, it is involved also in several faster lower level actions. Hence, we propose a process algebra with operations and with a semantics aimed at dealing with these aspects of multiscale modelling. We study behavioural equivalences for such an algebra and give some examples
Data-driven modelling of biological multi-scale processes
Biological processes involve a variety of spatial and temporal scales. A
holistic understanding of many biological processes therefore requires
multi-scale models which capture the relevant properties on all these scales.
In this manuscript we review mathematical modelling approaches used to describe
the individual spatial scales and how they are integrated into holistic models.
We discuss the relation between spatial and temporal scales and the implication
of that on multi-scale modelling. Based upon this overview over
state-of-the-art modelling approaches, we formulate key challenges in
mathematical and computational modelling of biological multi-scale and
multi-physics processes. In particular, we considered the availability of
analysis tools for multi-scale models and model-based multi-scale data
integration. We provide a compact review of methods for model-based data
integration and model-based hypothesis testing. Furthermore, novel approaches
and recent trends are discussed, including computation time reduction using
reduced order and surrogate models, which contribute to the solution of
inference problems. We conclude the manuscript by providing a few ideas for the
development of tailored multi-scale inference methods.Comment: This manuscript will appear in the Journal of Coupled Systems and
Multiscale Dynamics (American Scientific Publishers
Bone Remodelling in BioShape
AbstractMany biological phenomena are inherently multiscale, i.e. they are characterised by interactions involving different scales at the same time. This is the case of bone remodelling, where macroscopic behaviour (at organ and tissue scale) and microstructure (at cell scale) strongly influence each other. Consequently, several approaches have been defined to model such a process at different spatial and temporal levels and, in particular, in terms of continuum properties, abstracting in this way from a realistic – and more complex – cellular scenario. While a large amount of information is available to validate such models separately, more work is needed to integrate all levels fully in a faithful multiscale model.In this scenario, we propose the use of BioShape, a 3D particle-based, scale-independent, geometry and space oriented simulator. It is used to define and integrate a cell and tissue scale model for bone remodelling in terms of shapes equipped with perception, interaction and movement capabilities. Their in-silico simulation allows for tuning continuum-based tissutal and cellular models, as well as for better understanding – both in qualitative and in quantitative terms – the blurry synergy between mechanical and metabolic factors triggering bone remodelling
Differentiated cell behavior: a multiscale approach using measure theory
This paper deals with the derivation of a collective model of cell
populations out of an individual-based description of the underlying physical
particle system. By looking at the spatial distribution of cells in terms of
time-evolving measures, rather than at individual cell paths, we obtain an
ensemble representation stemming from the phenomenological behavior of the
single component cells. In particular, as a key advantage of our approach, the
scale of representation of the system, i.e., microscopic/discrete vs.
macroscopic/continuous, can be chosen a posteriori according only to the
spatial structure given to the aforesaid measures. The paper focuses in
particular on the use of different scales based on the specific functions
performed by cells. A two-population hybrid system is considered, where cells
with a specialized/differentiated phenotype are treated as a discrete
population of point masses while unspecialized/undifferentiated cell aggregates
are represented with a continuous approximation. Numerical simulations and
analytical investigations emphasize the role of some biologically relevant
parameters in determining the specific evolution of such a hybrid cell system.Comment: 25 pages, 6 figure
Statistical extraction of process zones and representative subspaces in fracture of random composite
We propose to identify process zones in heterogeneous materials by tailored
statistical tools. The process zone is redefined as the part of the structure
where the random process cannot be correctly approximated in a low-dimensional
deterministic space. Such a low-dimensional space is obtained by a spectral
analysis performed on pre-computed solution samples. A greedy algorithm is
proposed to identify both process zone and low-dimensional representative
subspace for the solution in the complementary region. In addition to the
novelty of the tools proposed in this paper for the analysis of localised
phenomena, we show that the reduced space generated by the method is a valid
basis for the construction of a reduced order model.Comment: Submitted for publication in International Journal for Multiscale
Computational Engineerin
Proto-Plasm: parallel language for adaptive and scalable modelling of biosystems
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
Chaste: a test-driven approach to software development for biological modelling
Chaste (‘Cancer, heart and soft-tissue environment’) is a software library and a set of test suites for computational simulations in the domain of biology. Current functionality has arisen from modelling in the fields of cancer, cardiac physiology and soft-tissue mechanics. It is released under the LGPL 2.1 licence.\ud
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Chaste has been developed using agile programming methods. The project began in 2005 when it was reasoned that the modelling of a variety of physiological phenomena required both a generic mathematical modelling framework, and a generic computational/simulation framework. The Chaste project evolved from the Integrative Biology (IB) e-Science Project, an inter-institutional project aimed at developing a suitable IT infrastructure to support physiome-level computational modelling, with a primary focus on cardiac and cancer modelling
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