The first aim of simulation in virtual environment is to help biologists to have a better understanding of the simulated system. The cost of such simulation is significantly reduced compared to that of in vivo simulation. However, the inherent complexity of biological system makes it hard to simulate these systems on non-parallel architectures: models might be made of sub-models and take several scales into account; the number of simulated entities may be quite large. Today, graphics cards are used for general (...) purpose computing which has been made easier thanks to frameworks like CUDA or OpenCL. Parallelization of models may however not be easy: parallel computer programing skills are often required; several hardware architectures may be used to execute models. In this paper, we present the software architecture we built in order to implement various models able to simulate multi-cellular system. This architecture is modular and it implements data structures adapted for graphics processing units architectures. It allows efficient simulation of biological mechanisms. (shrink)

New concepts may prove necessary to profit from the avalanche of sequence data on the genome, transcriptome, proteome and interactome and to relate this information to cell physiology. Here, we focus on the concept of large activity-based structures, or hyperstructures, in which a variety of types of molecules are brought together to perform a function. We review the evidence for the existence of hyperstructures responsible for the initiation of DNA replication, the sequestration of newly replicated origins of replication, cell division (...) and for metabolism. The processes responsible for hyperstructure formation include changes in enzyme affinities due to metabolite-induction, lipid-protein affinities, elevated local concentrations of proteins and their binding sites on DNA and RNA, and transertion. Experimental techniques exist that can be used to study hyperstructures and we review some of the ones less familiar to biologists. Finally, we speculate on how a variety of in silico approaches involving cellular automata and multi-agent systems could be combined to develop new concepts in the form of an Integrated cell (I-cell) which would undergo selection for growth and survival in a world of artificial microbiology. (shrink)

Simulation of complex biological systems with agent-based models is becoming more relevant with the increase in Graphics Processing Unit power. In those simulations, up to millions of virtual cells are individually computed, involving daunting processing times. An important part of computational models is the algorithm that manages how agents perceive their surroundings. This can be particularly problematic in three-dimensional environments where agents have deformable virtual membranes. This article presents a GPU algorithm that gives the possibility for agents to integrate the (...) signals scattered on their virtual membrane. It is detailed to be coded in languages like OpenCL or Cuda. Its performances are tested to show its speed with current GPU devices. Finally, it was implemented inside an existing software to test and illustrate the possibilities it offers. (shrink)

While the control of cell migration by biochemical and biophysical factors is largely documented, a precise quantification of cell migration parameters in different experimental contexts is still questionable. Indeed, these phenomenological parameters can be evaluated from data obtained either at the cell population level or at the individual cell level. However, the range within which both characterizations of cell migration are equivalent remains unclear. We analyse here to which extent both sources of data could be integrated within a unified description (...) of cell migration by considering the motility of the endothelial cell line EAhy926. Using time-lapse video-microscopy and associated analysis of digital image time series, we quantified EAhy926 random motility coefficient, migration speed and trajectory persistence time in two different migration assays: the in vitro wound healing assay, and the cell-populated agarose drop assay. In order to analyse the agreement between independent quantifications of cell motility based either on individual cell analysis or cell population dynamic analysis, a theoretical multi-agents cellular model was developed and discussed as a possible theoretical framework able to unify these multi-scale data. Model simulations especially reveal the potential bias induced by cell proliferation and cell-cell adhesion when cell migration parameters are estimated from the extensively used in vitro wound healing assay. (shrink)