12,466 research outputs found
Stochastic Calculus of Wrapped Compartments
The Calculus of Wrapped Compartments (CWC) is a variant of the Calculus of
Looping Sequences (CLS). While keeping the same expressiveness, CWC strongly
simplifies the development of automatic tools for the analysis of biological
systems. The main simplification consists in the removal of the sequencing
operator, thus lightening the formal treatment of the patterns to be matched in
a term (whose complexity in CLS is strongly affected by the variables matching
in the sequences).
We define a stochastic semantics for this new calculus. As an application we
model the interaction between macrophages and apoptotic neutrophils and a
mechanism of gene regulation in E.Coli
Process Calculi Abstractions for Biology
Several approaches have been proposed to model biological systems by means of the formal techniques and tools available in computer science. To mention just a few of them, some representations are inspired by Petri Nets theory, and some other by stochastic processes. A most recent approach consists in interpreting the living entities as terms of process calculi where the behavior of the represented systems can be inferred by applying syntax-driven rules. A comprehensive picture of the state of the art of the process calculi approach to biological modeling is still missing. This paper goes in the direction of providing such a picture by presenting a comparative survey of the process calculi that have been used and proposed to describe the behavior of living entities. This is the preliminary version of a paper that was published in Algorithmic Bioprocesses. The original publication is available at http://www.springer.com/computer/foundations/book/978-3-540-88868-
Formal executable descriptions of biological systems
The similarities between systems of living entities and systems of concurrent processes may support biological experiments in silico. Process calculi offer a formal framework to describe biological systems, as well as to analyse their behaviour, both from a qualitative and a quantitative point of view. A couple of little examples help us in showing how this can be done. We mainly focus our attention on the qualitative and quantitative aspects of the considered biological systems, and briefly illustrate which kinds of analysis are possible. We use a known stochastic calculus for the first example. We then present some statistics collected by repeatedly running the specification, that turn out to agree with those obtained by experiments in vivo. Our second example motivates a richer calculus. Its stochastic extension requires a non trivial machinery to faithfully reflect the real dynamic behaviour of biological systems
Theoretical basis of the community effect in development
Peer reviewedPublisher PD
A framework for protein and membrane interactions
We introduce the BioBeta Framework, a meta-model for both protein-level and
membrane-level interactions of living cells. This formalism aims to provide a
formal setting where to encode, compare and merge models at different
abstraction levels; in particular, higher-level (e.g. membrane) activities can
be given a formal biological justification in terms of low-level (i.e.,
protein) interactions. A BioBeta specification provides a protein signature
together a set of protein reactions, in the spirit of the kappa-calculus.
Moreover, the specification describes when a protein configuration triggers one
of the only two membrane interaction allowed, that is "pinch" and "fuse". In
this paper we define the syntax and semantics of BioBeta, analyse its
properties, give it an interpretation as biobigraphical reactive systems, and
discuss its expressivity by comparing with kappa-calculus and modelling
significant examples. Notably, BioBeta has been designed after a bigraphical
metamodel for the same purposes. Hence, each instance of the calculus
corresponds to a bigraphical reactive system, and vice versa (almost).
Therefore, we can inherith the rich theory of bigraphs, such as the automatic
construction of labelled transition systems and behavioural congruences
Cell Cycle Control in Eukaryotes: a BioSpi model
This paper presents a stochastic model of the cell cycle control in eukaryotes. The framework used is based on stochastic process algebras for mobile systems. The automatic tool used in the simulation is the BioSpi. We compare our approach with classical ODE specications
Compositionality, stochasticity and cooperativity in dynamic models of gene regulation
We present an approach for constructing dynamic models for the simulation of
gene regulatory networks from simple computational elements. Each element is
called a ``gene gate'' and defines an input/output-relationship corresponding
to the binding and production of transcription factors. The proposed reaction
kinetics of the gene gates can be mapped onto stochastic processes and the
standard ode-description. While the ode-approach requires fixing the system's
topology before its correct implementation, expressing them in stochastic
pi-calculus leads to a fully compositional scheme: network elements become
autonomous and only the input/output relationships fix their wiring. The
modularity of our approach allows to pass easily from a basic first-level
description to refined models which capture more details of the biological
system. As an illustrative application we present the stochastic repressilator,
an artificial cellular clock, which oscillates readily without any cooperative
effects.Comment: 15 pages, 8 figures. Accepted by the HFSP journal (13/09/07
Parallel BioScape: A Stochastic and Parallel Language for Mobile and Spatial Interactions
BioScape is a concurrent language motivated by the biological landscapes
found at the interface of biology and biomaterials. It has been motivated by
the need to model antibacterial surfaces, biofilm formation, and the effect of
DNAse in treating and preventing biofilm infections. As its predecessor, SPiM,
BioScape has a sequential semantics based on Gillespie's algorithm, and its
implementation does not scale beyond 1000 agents. However, in order to model
larger and more realistic systems, a semantics that may take advantage of the
new multi-core and GPU architectures is needed. This motivates the introduction
of parallel semantics, which is the contribution of this paper: Parallel
BioScape, an extension with fully parallel semantics.Comment: In Proceedings MeCBIC 2012, arXiv:1211.347
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