381 research outputs found
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
Efficient negation using abstract interpretation
While negation has been a very active área of research in
logic programming, comparatively few papers have been devoted to implementation issues. Furthermore, the negation-related capabilities of current Prolog systems are limited. We recently presented a novel method for incorporating negation in a Prolog compiler which takes a number of
existing methods (some modified and improved by us) and uses them in a combined fashion. The method makes use of information provided by a global analysis of the source code. Our previous work focused on the systematic description of the techniques and the reasoning about correctness and completeness of the method, but provided no experimental evidence to evalúate the proposal. In this paper, we report on an implementation, using the Ciao Prolog system preprocessor, and provide experimental data which indicates that the method is not only feasible but also quite promising from the efficiency point of view. In addition, the tests have provided new insight as to how to improve the proposal further. Abstract interpretation techniques are shown to offer important improvements in this application
Process algebra modelling styles for biomolecular processes
We investigate how biomolecular processes are modelled in process algebras, focussing on chemical reactions. We consider various modelling styles and how design decisions made in the definition of the process algebra have an impact on how a modelling style can be applied. Our goal is to highlight the often implicit choices that modellers make in choosing a formalism, and illustrate, through the use of examples, how this can affect expressability as well as the type and complexity of the analysis that can be performed
Multiple verification in computational modeling of bone pathologies
We introduce a model checking approach to diagnose the emerging of bone
pathologies. The implementation of a new model of bone remodeling in PRISM has
led to an interesting characterization of osteoporosis as a defective bone
remodeling dynamics with respect to other bone pathologies. Our approach allows
to derive three types of model checking-based diagnostic estimators. The first
diagnostic measure focuses on the level of bone mineral density, which is
currently used in medical practice. In addition, we have introduced a novel
diagnostic estimator which uses the full patient clinical record, here
simulated using the modeling framework. This estimator detects rapid (months)
negative changes in bone mineral density. Independently of the actual bone
mineral density, when the decrease occurs rapidly it is important to alarm the
patient and monitor him/her more closely to detect insurgence of other bone
co-morbidities. A third estimator takes into account the variance of the bone
density, which could address the investigation of metabolic syndromes, diabetes
and cancer. Our implementation could make use of different logical combinations
of these statistical estimators and could incorporate other biomarkers for
other systemic co-morbidities (for example diabetes and thalassemia). We are
delighted to report that the combination of stochastic modeling with formal
methods motivate new diagnostic framework for complex pathologies. In
particular our approach takes into consideration important properties of
biosystems such as multiscale and self-adaptiveness. The multi-diagnosis could
be further expanded, inching towards the complexity of human diseases. Finally,
we briefly introduce self-adaptiveness in formal methods which is a key
property in the regulative mechanisms of biological systems and well known in
other mathematical and engineering areas.Comment: In Proceedings CompMod 2011, arXiv:1109.104
A novel breast cancer-associated BRIP1 (FANCJ/BACH1) germ-line mutation impairs protein stability and function
Multiscale Bone Remodelling with Spatial P Systems
Many biological phenomena are inherently multiscale, i.e. they are
characterized by interactions involving different spatial and temporal scales
simultaneously. Though several approaches have been proposed to provide
"multilayer" models, only Complex Automata, derived from Cellular Automata,
naturally embed spatial information and realize multiscaling with
well-established inter-scale integration schemas. Spatial P systems, a variant
of P systems in which a more geometric concept of space has been added, have
several characteristics in common with Cellular Automata. We propose such a
formalism as a basis to rephrase the Complex Automata multiscaling approach
and, in this perspective, provide a 2-scale Spatial P system describing bone
remodelling. The proposed model not only results to be highly faithful and
expressive in a multiscale scenario, but also highlights the need of a deep and
formal expressiveness study involving Complex Automata, Spatial P systems and
other promising multiscale approaches, such as our shape-based one already
resulted to be highly faithful.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005
An Approach to the Bio-Inspired Control of Self-reconfigurable Robots
Self-reconfigurable robots are robots built by modules which
can move in relationship to each other. This ability of changing its physical
form provides the robots a high level of adaptability and robustness.
Given an initial configuration and a goal configuration of the robot, the
problem of self-regulation consists on finding a sequence of module moves
that will reconfigure the robot from the initial configuration to the goal
configuration. In this paper, we use a bio-inspired method for studying
this problem which combines a cluster-flow locomotion based on cellular
automata together with a decentralized local representation of the
spatial geometry based on membrane computing ideas. A promising 3D
software simulation and a 2D hardware experiment are also presented.National Natural Science Foundation of China No. 6167313
Parametric timed model checking for guaranteeing timed opacity
Information leakage can have dramatic consequences on systems security. Among
harmful information leaks, the timing information leakage is the ability for an
attacker to deduce internal information depending on the system execution time.
We address the following problem: given a timed system, synthesize the
execution times for which one cannot deduce whether the system performed some
secret behavior. We solve this problem in the setting of timed automata (TAs).
We first provide a general solution, and then extend the problem to parametric
TAs, by synthesizing internal timings making the TA secure. We study
decidability, devise algorithms, and show that our method can also apply to
program analysis.Comment: This is the author (and extended) version of the manuscript of the
same name published in the proceedings of ATVA 2019. This work is partially
supported by the ANR national research program PACS (ANR-14-CE28-0002), the
ANR-NRF research program (ProMiS) and by ERATO HASUO Metamathematics for
Systems Design Project (No. JPMJER1603), JS
Embryonic stem cell-derived CD166+ precursors develop into fully functional sinoatrial-like cells
Rationale: A cell-based biological pacemaker is based on the differentiation of stem cells and the selection of a population displaying the molecular and functional properties of native sinoatrial node (SAN) cardiomyocytes. So far, such selection has been hampered by the lack of proper markers. CD166 is specifically but transiently expressed in the mouse heart tube and sinus venosus, the prospective SAN.
Objective: We have explored the possibility of using CD166 expression for isolating SAN progenitors from differentiating embryonic stem cells.
Methods and Results: We found that in embryonic day 10.5 mouse hearts, CD166 and HCN4, markers of the pacemaker tissue, are coexpressed. Sorting embryonic stem cells for CD166 expression at differentiation day 8 selects a population of pacemaker precursors. CD166(+) cells express high levels of genes involved in SAN development (Tbx18, Tbx3, Isl-1, Shox2) and function (Cx30.2, HCN4, HCN1, CaV1.3) and low levels of ventricular genes (Cx43, Kv4.2, HCN2, Nkx2.5). In culture, CD166(+) cells form an autorhythmic syncytium composed of cells morphologically similar to and with the electrophysiological properties of murine SAN myocytes. Isoproterenol increases (+57%) and acetylcholine decreases (-23%) the beating rate of CD166-selected cells, which express the -adrenergic and muscarinic receptors. In cocultures, CD166-selected cells are able to pace neonatal ventricular myocytes at a rate faster than their own. Furthermore, CD166(+) cells have lost pluripotency genes and do not form teratomas in vivo.
Conclusions: We demonstrated for the first time the isolation of a nonteratogenic population of cardiac precursors able to mature and form a fully functional SAN-like tissue
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