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Search Results: 1 - 10 of 10524 matches for " Alexandre Donzé "
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A Model of the Cellular Iron Homeostasis Network Using Semi-Formal Methods for Parameter Space Exploration
Nicolas Mobilia,Alexandre Donzé,Jean Marc Moulis,éric Fanchon
Electronic Proceedings in Theoretical Computer Science , 2012, DOI: 10.4204/eptcs.92.4
Abstract: This paper presents a novel framework for the modeling of biological networks. It makes use of recent tools analyzing the robust satisfaction of properties of (hybrid) dynamical systems. The main challenge of this approach as applied to biological systems is to get access to the relevant parameter sets despite gaps in the available knowledge. An initial estimate of useful parameters was sought by formalizing the known behavior of the biological network in the STL logic using the tool Breach. Then, once a set of parameter values consistent with known biological properties was found, we tried to locally expand it into the largest possible valid region. We applied this methodology in an effort to model and better understand the complex network regulating iron homeostasis in mammalian cells. This system plays an important role in many biological functions, including erythropoiesis, resistance against infections, and proliferation of cancer cells.
Control Improvisation
Daniel J. Fremont,Alexandre Donzé,Sanjit A. Seshia,David Wessel
Computer Science , 2014,
Abstract: We formalize and analyze a new automata-theoretic problem termed control improvisation. Given an automaton, the problem is to produce an improviser, a probabilistic algorithm that randomly generates words in its language, subject to two additional constraints: the satisfaction of an admissibility predicate, and the exhibition of a specified amount of randomness. Control improvisation has multiple applications, including, for example, generating musical improvisations that satisfy rhythmic and melodic constraints, where admissibility is determined by some bounded divergence from a reference melody. We analyze the complexity of the control improvisation problem, giving cases where it is efficiently solvable and cases where it is #P-hard or undecidable. We also show how symbolic techniques based on Boolean satisfiability (SAT) solvers can be used to approximately solve some of the intractable cases.
Producing a Set of Models for the Iron Homeostasis Network
Nicolas Mobilia,Alexandre Donzé,Jean Marc Moulis,éric Fanchon
Computer Science , 2013, DOI: 10.4204/EPTCS.125.7
Abstract: This paper presents a method for modeling biological systems which combines formal techniques on intervals, numerical simulations and satisfaction of Signal Temporal Logic (STL) formulas. The main modeling challenge addressed by this approach is the large uncertainty in the values of the parameters due to the experimental difficulties of getting accurate biological data. This method considers intervals for each parameter and a formal description of the expected behavior of the model. In a first step, it produces reduced intervals of possible parameter values. Then by performing a systematic search in these intervals, it defines sets of parameter values used in the next step. This procedure aims at finding a sub-space where the model robustly behaves as expected. We apply this method to the modeling of the cellular iron homeostasis network in erythroid progenitors. The produced model describes explicitly the regulation mechanism which acts at the translational level.
Robustness Analysis and Behavior Discrimination in Enzymatic Reaction Networks
Alexandre Donzé,Eric Fanchon,Lucie Martine Gattepaille,Oded Maler,Philippe Tracqui
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0024246
Abstract: Characterizing the behavior and robustness of enzymatic networks with numerous variables and unknown parameter values is a major challenge in biology, especially when some enzymes have counter-intuitive properties or switch-like behavior between activation and inhibition. In this paper, we propose new methodological and tool-supported contributions, based on the intuitive formalism of temporal logic, to express in a rigorous manner arbitrarily complex dynamical properties. Our multi-step analysis allows efficient sampling of the parameter space in order to define feasible regions in which the model exhibits imposed or experimentally observed behaviors. In a first step, an algorithmic methodology involving sensitivity analysis is conducted to determine bifurcation thresholds for a limited number of model parameters or initial conditions. In a second step, this boundary detection is supplemented by a global robustness analysis, based on quasi-Monte Carlo approach that takes into account all model parameters. We apply this method to a well-documented enzymatic reaction network describing collagen proteolysis by matrix metalloproteinase MMP2 and membrane type 1 metalloproteinase (MT1-MMP) in the presence of tissue inhibitor of metalloproteinase TIMP2. For this model, our method provides an extended analysis and quantification of network robustness toward paradoxical TIMP2 switching activity between activation or inhibition of MMP2 production. Further implication of our approach is illustrated by demonstrating and analyzing the possible existence of oscillatory behaviors when considering an extended open configuration of the enzymatic network. Notably, we construct bifurcation diagrams that specify key parameters values controlling the co-existence of stable steady and non-steady oscillatory proteolytic dynamics.
Control Improvisation with Probabilistic Temporal Specifications
Ilge Akkaya,Daniel J. Fremont,Rafael Valle,Alexandre Donzé,Edward A. Lee,Sanjit A. Seshia
Computer Science , 2015,
Abstract: We consider the problem of generating randomized control sequences for complex networked systems typically actuated by human agents. Our approach leverages a concept known as control improvisation, which is based on a combination of data-driven learning and controller synthesis from formal specifications. We learn from existing data a generative model (for instance, an explicit-duration hidden Markov model, or EDHMM) and then supervise this model in order to guarantee that the generated sequences satisfy some desirable specifications given in Probabilistic Computation Tree Logic (PCTL). We present an implementation of our approach and apply it to the problem of mimicking the use of lighting appliances in a residential unit, with potential applications to home security and resource management. We present experimental results showing that our approach produces realistic control sequences, similar to recorded data based on human actuation, while satisfying suitable formal requirements.
Robust Online Monitoring of Signal Temporal Logic
Jyotirmoy V. Deshmukh,Alexandre Donzé,Shromona Ghosh,Xiaoqing Jin,Garvit Juniwal,Sanjit A. Seshia
Computer Science , 2015,
Abstract: Signal Temporal Logic (STL) is a formalism used to rigorously specify requirements of cyberphysical systems (CPS), i.e., systems mixing digital or discrete components in interaction with a continuous environment or analog com- ponents. STL is naturally equipped with a quantitative semantics which can be used for various purposes: from assessing the robustness of a specification to guiding searches over the input and parameter space with the goal of falsifying the given property over system behaviors. Algorithms have been proposed and implemented for offline computation of such quantitative semantics, but only few methods exist for an online setting, where one would want to monitor the satisfaction of a formula during simulation. In this paper, we formalize a semantics for robust online monitoring of partial traces, i.e., traces for which there might not be enough data to decide the Boolean satisfaction (and to compute its quantitative counterpart). We propose an efficient algorithm to compute it and demonstrate its usage on two large scale real-world case studies coming from the automotive domain and from CPS education in a Massively Open Online Course (MOOC) setting. We show that savings in computationally expensive simulations far outweigh any overheads incurred by an online approach.
Automatic Assessment of Expanded Disability Status Scale (EDSS) in Multiple Sclerosis Using a Decision Tree  [PDF]
Hua Cao, Olivier Agnani, Laurent Peyrodie, Cécile Donzé
Engineering (ENG) , 2013, DOI: 10.4236/eng.2013.510B116
Abstract:

The expanded disability status scale (EDSS) is frequently used to classify the patients with multiple sclerosis (MS). We presented in this paper a novel method to automatically assess the EDSS score from posturologic data (center of pres-sure signals) using a decision tree. Two groups of participants (one for learning and the other for test) with EDSS rang-ing from 0 to 4.5 performed our balance experiment with eyes closed. Two linear measures (the length and the surface) and twelve non-linear measures (the recurrence rate, the Shannon entropy, the averaged diagonal line length and the trapping time for the position, the instantaneous velocity and the instantaneous acceleration of the center of pressure respectively) were calculated for all the participants. Several decision trees were constructed with learning data and tested with test data. By comparing clinical and estimated EDSS scores in the test group, we selected one decision tree with five measures which revealed a 75% of agreement. The results have signified that our tree model is able to auto-matically assess the EDSS scores and that it is possible to distinguish the EDSS scores by using linear and non-linear postural sway measures.


Editorial Special Issue on “Energetic Complementarity”  [PDF]
Alexandre Beluco
Energy and Power Engineering (EPE) , 2017, DOI: 10.4236/epe.2017.99033
Abstract: This editorial presents the motivations that were the focus of the papers that make up this Special Issue on energetic complementarity. The articles deal with the application of the concept of energetic complementarity in time under certain conditions and with the proposition of new means to evaluate complementarity in time between more than two renewable energy resources. An article further proposes a method for establishing energetic complementarity in space, a concept that is important and necessary for management and planning of energy resources but does not yet have tools that allow it to be quantified and handled appropriately. In addition, two letters to the editor discuss issues that still need to be matured for a better understanding and application of the concept of energetic complementarity, both in time and space.
Minamata Disease—Review  [PDF]
Alexandre Semionov
World Journal of Neuroscience (WJNS) , 2018, DOI: 10.4236/wjns.2018.82016
Abstract: Minamata disease is the name given to a neurological syndrome caused by or-ganic mercury intoxication. Most commonly it results from consumption of methylmercury contaminated seafood and in severe cases is classically mani-fested by concentric constriction of the visual fields, ataxia and sensory dis-turbance in the distal extremities. The radiographic and neuropathological find-ings parallel the clinical picture and typically consist of lesions selectively in-volving the visual cortex, cerebellum and postecentral gyri.
On Approximating the Gradient of the Value Function  [PDF]
Alexandre Dmitriev
Theoretical Economics Letters (TEL) , 2019, DOI: 10.4236/tel.2019.91011
Abstract:

The optimality conditions for macroeconomic problems with limited commitment often contain partial derivatives of the optimal value function, corresponding to the outside option. This paper contributes to the literature on recursive contracts by proposing an algorithm for approximating the gradient of the value function using simulation-based methods. Our method combines numerical solution and simulation of the model, Monte-Carlo integration and numerical differentiation. It does not suffer from the curse of dimensionality and is therefore convenient for models involving many state variables. The algorithm inherits the speed and accuracy limitations of the numerical solution method it relies on. Our accuracy analysis is limited to a few classical examples from macroeconomic literature.

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