A5023902666- Gene Regulatory Network Analysis
- Formal Methods in Verification
- Microbial Metabolic Engineering and Bioproduction
- Petri Nets in System Modeling
- Bioinformatics and Genomic Networks
- Logic, Reasoning, and Knowledge
- DNA and Biological Computing
- Business Process Modeling and Analysis
- Single-cell and spatial transcriptomics
- AI-based Problem Solving and Planning
- Online Learning and Analytics
- Evolutionary Algorithms and Applications
- Semantic Web and Ontologies
- Embedded Systems Design Techniques
- Open Education and E-Learning
- Protein Structure and Dynamics
- Simulation Techniques and Applications
- French Language Learning Methods
- Machine Learning and Algorithms
- Experimental Learning in Engineering
- Model-Driven Software Engineering Techniques
- Receptor Mechanisms and Signaling
- Service-Oriented Architecture and Web Services
- Real-Time Systems Scheduling
- E-Learning and Knowledge Management
École Centrale de Nantes
2015-2024
Centre National de la Recherche Scientifique
2012-2024
Laboratoire des Sciences du Numérique de Nantes
2017-2024
National Institute of Informatics
2013-2024
Nantes Université
2018-2023
The Graduate University for Advanced Studies, SOKENDAI
2023
École nationale supérieure de techniques avancées Bretagne
2013-2014
Département d'Informatique
2014
The analysis of the dynamics Biological Regulatory Networks (BRNs) requires innovative methods to cope with state-space explosion. This paper settles an original approach for deciding reachability properties based on Process Hitting , which is a framework suitable modelling dynamical complex systems. In particular, has been shown be interest in providing compact models BRNs discrete values. splits finite number processes into so-called sorts and describes way each process able act upon (that...
Abstract The response to respiratory viruses varies substantially between individuals, and there are currently no known molecular predictors from the early stages of infection. Here we conduct a community-based analysis determine whether pre- or post-exposure factors could predict physiologic responses viral exposure. Using peripheral blood gene expression profiles collected healthy subjects prior exposure one four (H1N1, H3N2, Rhinovirus, RSV), as well up 24 h following exposure, find that...
This paper addresses the problem of finding attractors in biological regulatory networks. We focus here on non-deterministic synchronous and asynchronous multi-valued networks, modeled using automata networks (AN). AN is a general well-suited formalism to study complex interactions between different components (genes, proteins,...). An attractor minimal trap domain, that is, part state-transition graph cannot be escaped. Such structures are terminal dynamics take form steady states...
Boolean networks are a widely used model to represent gene interactions and global dynamical behavior of genetic regulatory networks. To understand the memory effect involved in some between biological components, it is necessary include delayed influences model. In this paper, we present logical method learn such models from sequences expression data. This analyzes each sequence one-by-one iteratively construct network that captures dynamics these observations. illustrate merits approach,...
Delayed effects are important in modeling biological systems, and timed Boolean networks have been proposed for such a framework. Yet it is not an easy task to design models with delays precisely. Recently, attempt learn has made Ribeiro et al 2015 the framework of learning state transition rules from time-series data. However, this approach still two limitations: (1) The maximum delay be given as input algorithm, (2) possible value each assumed Boolean, i.e., twovalued. In paper, we extend...
The Process Hitting is a recently introduced framework designed for the modelling of concurrent systems. Its originality lies in compact representation both components model and its corresponding actions: each action can modify status component, conditioned by at most one other component. This allowed to define very efficient static analysis based on local causality compute reachability properties. However, case cooperations between (for example, when two are supposed interact with third...
The combination of numerous simple influences between the components a Biological Regulatory Network (BRN) often leads to behaviors that cannot be grasped intuitively. They thus call for development proper mathematical methods delineate their dynamical properties. As consequence, formal and computer tools modeling simulation BRNs become essential. Our recently introduced discrete formalism called Process Hitting (PH), restriction synchronous automata networks, is notably suitable such study....
The stochastic \pi-calculus is a formalism that has been used for modeling complex dynamical systems where the stochasticity and delay of transitions are important features, such as in case biochemical reactions. Commonly, durations within models follow an exponential law. underlying dynamics expressed terms continuous-time Markov chains, which can then be efficiently simulated model-checked. However, law comes with huge variance, making it difficult to model accurate temporal constraints....
Analysing dynamics of large biological regulatory networks (BRNs) calls for innovative methods to cope with the state space explosion. Static analysis and abstract interpretation techniques seem promising approaches. In this paper, we address Process Hitting framework, that has been shown interest model BRNs discrete values. We propose take profit from particular structures build efficient static analyses. introduce a novel original method decide reachability component within BRN modelled in...
With this contribution, we aim to draw a comprehensive classification of Petri nets with stopwatches w.r.t. expressiveness and decidability issues. This topic is too ambitious be summarized in single paper. That why present our results