8 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
Modelling the Dynamics of an Aedes albopictus Population
We present a methodology for modelling population dynamics with formal means
of computer science. This allows unambiguous description of systems and
application of analysis tools such as simulators and model checkers. In
particular, the dynamics of a population of Aedes albopictus (a species of
mosquito) and its modelling with the Stochastic Calculus of Looping Sequences
(Stochastic CLS) are considered. The use of Stochastic CLS to model population
dynamics requires an extension which allows environmental events (such as
changes in the temperature and rainfalls) to be taken into account. A simulator
for the constructed model is developed via translation into the specification
language Maude, and used to compare the dynamics obtained from the model with
real data.Comment: In Proceedings AMCA-POP 2010, arXiv:1008.314
Modelling Cell Cycle using Different Levels of Representation
Understanding the behaviour of biological systems requires a complex setting
of in vitro and in vivo experiments, which attracts high costs in terms of time
and resources. The use of mathematical models allows researchers to perform
computerised simulations of biological systems, which are called in silico
experiments, to attain important insights and predictions about the system
behaviour with a considerably lower cost. Computer visualisation is an
important part of this approach, since it provides a realistic representation
of the system behaviour. We define a formal methodology to model biological
systems using different levels of representation: a purely formal
representation, which we call molecular level, models the biochemical dynamics
of the system; visualisation-oriented representations, which we call visual
levels, provide views of the biological system at a higher level of
organisation and are equipped with the necessary spatial information to
generate the appropriate visualisation. We choose Spatial CLS, a formal
language belonging to the class of Calculi of Looping Sequences, as the
formalism for modelling all representation levels. We illustrate our approach
using the budding yeast cell cycle as a case study
Modelling Biological Systems From Molecular Interactions to Population Dynamics
Biological systems are examples of complex systems, which consist of several interacting components. Understanding the behaviour of such systems requires a multidisciplinary approach that encompasses biology, mathematics, computer science, physiscs and chemistry. New research areas are emerging as the result of this multidisciplinarity, such as bioinformatics, systems biology and computational biology. Computer science plays an important role in the newly emerging research areas by offerring techniques, algorithms, languages and software to solve research problems efficiently. On the other hand, the efforts to solve these research problems stimulate the development of new and better computer science techniques, algorithms, languages and software.
This thesis describes our approach in modelling biological systems as a way to better understand their complex behaviours. Our approach is based on the Calculi of Looping Sequences, a class of formalisms originally developed to model biological systems involving cells and their membrane-based structures. We choose Stochastic CLS and Spatial CLS, two variants of the calculi that support quantitative analysis of the model, and define an approach that support simulation, statistical model-checking and visualisation as analysis techniques. Moreover, we found out that this class of formalisms can be easily extended to model population dynamics of animals, a kind of biological systems that does not involve membrane-based structures
Translating Stochastic CLS into Maude
AbstractThis paper describes preliminary results on the application of statistical model-checking to systems described with Stochastic CLS. Stochastic CLS is a formalism based on term rewriting that allows biomolecular systems to be described by taking into account their structure and by allowing very general events to be modelled. Statistical model-checking is an analysis technique that permits properties of a system to be studied on the results of a number of stochastic simulations. We choose Real-Time Maude as a tool that supports the modelling and analysis of systems with real-time properties. We adapt Gillespie's algorithm for simulating chemical systems into our approach. The resulting method is applied to analyse some simple examples and a model of the lactose operon regulation in E.coli