37 research outputs found
Discrete and continuous time simulations of spatial ecological processes predict different final population sizes and interspecific competition outcomes
Cellular automata (CAs) are commonly used to simulate spatial processes in ecology. Although appropriate for modelling events that occur at discrete time points, they are also routinely used to model biological processes that take place continuously. We report on a study comparing predictions of discrete time CA models to those of their continuous time counterpart. Specifically, we investigate how the decision to model time discretely or continuously affects predictions regarding long-run population sizes, the probability of extinction and interspecific competition. We show effects on predicted ecological outcomes, finding quantitative differences in all cases and in the case of interspecific competition, additional qualitative differences in predictions regarding species dominance. Our findings demonstrate that qualitative conclusions drawn from spatial simulations can be critically dependent on the decision to model time discretely or continuously. Contrary to our expectations, simulating in continuous time did not incur a heavy computational penalty. We also raise ecological questions on the relative benefits of reproductive strategies that take place in discrete and continuous time
Projective and Coarse Projective Integration for Problems with Continuous Symmetries
Temporal integration of equations possessing continuous symmetries (e.g.
systems with translational invariance associated with traveling solutions and
scale invariance associated with self-similar solutions) in a ``co-evolving''
frame (i.e. a frame which is co-traveling, co-collapsing or co-exploding with
the evolving solution) leads to improved accuracy because of the smaller time
derivative in the new spatial frame. The slower time behavior permits the use
of {\it projective} and {\it coarse projective} integration with longer
projective steps in the computation of the time evolution of partial
differential equations and multiscale systems, respectively. These methods are
also demonstrated to be effective for systems which only approximately or
asymptotically possess continuous symmetries. The ideas of projective
integration in a co-evolving frame are illustrated on the one-dimensional,
translationally invariant Nagumo partial differential equation (PDE). A
corresponding kinetic Monte Carlo model, motivated from the Nagumo kinetics, is
used to illustrate the coarse-grained method. A simple, one-dimensional
diffusion problem is used to illustrate the scale invariant case. The
efficiency of projective integration in the co-evolving frame for both the
macroscopic diffusion PDE and for a random-walker particle based model is again
demonstrated
Stochastic kinetics of viral capsid assembly based on detailed protein structures
We present a generic computational framework for the simulation of viral
capsid assembly which is quantitative and specific. Starting from PDB files
containing atomic coordinates, the algorithm builds a coarse grained
description of protein oligomers based on graph rigidity. These reduced protein
descriptions are used in an extended Gillespie algorithm to investigate the
stochastic kinetics of the assembly process. The association rates are obtained
from a diffusive Smoluchowski equation for rapid coagulation, modified to
account for water shielding and protein structure. The dissociation rates are
derived by interpreting the splitting of oligomers as a process of graph
partitioning akin to the escape from a multidimensional well. This modular
framework is quantitative yet computationally tractable, with a small number of
physically motivated parameters. The methodology is illustrated using two
different viruses which are shown to follow quantitatively different assembly
pathways. We also show how in this model the quasi-stationary kinetics of
assembly can be described as a Markovian cascading process in which only a few
intermediates and a small proportion of pathways are present. The observed
pathways and intermediates can be related a posteriori to structural and
energetic properties of the capsid oligomers
Qualitative modelling and analysis of regulations in multi-cellular systems using Petri nets and topological collections
In this paper, we aim at modelling and analyzing the regulation processes in
multi-cellular biological systems, in particular tissues.
The modelling framework is based on interconnected logical regulatory
networks a la Rene Thomas equipped with information about their spatial
relationships. The semantics of such models is expressed through colored Petri
nets to implement regulation rules, combined with topological collections to
implement the spatial information.
Some constraints are put on the the representation of spatial information in
order to preserve the possibility of an enumerative and exhaustive state space
exploration.
This paper presents the modelling framework, its semantics, as well as a
prototype implementation that allowed preliminary experimentation on some
applications.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005
Particle simulation approach for subcellular dynamics and interactions of biological molecules
BACKGROUND: Spatio-temporal dynamics within cells can now be visualized at appropriate resolution, due to the advances in molecular imaging technologies. Even single-particle tracking (SPT) and single fluorophore video imaging (SFVI) are now being applied to observation of molecular-level dynamics. However, little is known concerning how molecular-level dynamics affect properties at the cellular level. RESULTS: We propose an algorithm designed for three-dimensional simulation of the reaction-diffusion dynamics of molecules, based on a particle model. Chemical reactions proceed through the interactions of particles in space, with activation energies determining the rates of these chemical reactions at each interaction. This energy-based model can include the cellular membrane, membranes of other organelles, and cytoskeleton. The simulation algorithm was tested for a reversible enzyme reaction model and its validity was confirmed. Snapshot images taken from simulated molecular interactions on the cell-surface revealed clustering domains (size ~0.2 μm) associated with rafts. Sample trajectories of raft constructs exhibited "hop diffusion". These domains corralled the diffusive motion of membrane proteins. CONCLUSION: These findings demonstrate that our approach is promising for modelling the localization properties of biological phenomena
Single-cell variability in multicellular organisms
While gene expression noise in single-celled organisms is well understood, it is less so in the context of tissues. Here the authors show that coupling between cells in tissues can increase or decrease cell-to-cell variability depending on the level of noise intrinsic to the regulatory networks
Electrical properties of hard plasma polymer C:H and composite metal/C:H films
Available from STL Prague, CZ / NTK - National Technical LibrarySIGLECZCzech Republi
Giuliano Bonfante. Baltistikos raštai. Scritti baltistici
Il volume raccoglie (nell'originale italiano e nella traduzione lituana) gli scritti baltistici di G. Bonfant