Sylvain Soliman
Research interests
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InterestsCell Cycle, Petri Nets, Model Checking, Constraint Programming, Logic Programming, Linear Logic, Circadian Rhythms
Publications
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Continuous valuations of temporal logic specifications with applications to parameter optimization and robustness measures.
Theor. Comput. Sci. 01/2011; 412:2827-2839.
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4.93Impact points
A graphical method for reducing and relating models in systems biology.
Bioinformatics (Oxford, England). 09/2010; 26(18):i575-81.
In Systems Biology, an increasing collection of models of various biological processes is currently developed and made available in publicly accessible repositories, such as biomodels.net for instance, through common exchange formats such as SBML. To date, however, there is no general method to rela... [more] In Systems Biology, an increasing collection of models of various biological processes is currently developed and made available in publicly accessible repositories, such as biomodels.net for instance, through common exchange formats such as SBML. To date, however, there is no general method to relate different models to each other by abstraction or reduction relationships, and this task is left to the modeler for re-using and coupling models. In mathematical biology, model reduction techniques have been studied for a long time, mainly in the case where a model exhibits different time scales, or different spatial phases, which can be analyzed separately. These techniques are however far too restrictive to be applied on a large scale in systems biology, and do not take into account abstractions other than time or phase decompositions. Our purpose here is to propose a general computational method for relating models together, by considering primarily the structure of the interactions and abstracting from their dynamics in a first step. We present a graph-theoretic formalism with node merge and delete operations, in which model reductions can be studied as graph matching problems. From this setting, we derive an algorithm for deciding whether there exists a reduction from one model to another, and evaluate it on the computation of the reduction relations between all SBML models of the biomodels.net repository. In particular, in the case of the numerous models of MAPK signalling, and of the circadian clock, biologically meaningful mappings between models of each class are automatically inferred from the structure of the interactions. We conclude on the generality of our graphical method, on its limits with respect to the representation of the structure of the interactions in SBML, and on some perspectives for dealing with the dynamics. The algorithms described in this article are implemented in the open-source software modeling platform BIOCHAM available at http://contraintes.inria.fr/biocham The models used in the experiments are available from http://www.biomodels.net/.
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4.41Impact points
A unique transformation from ordinary differential equations to reaction networks.
PloS one. 01/2010; 5(12):e14284.
Many models in Systems Biology are described as a system of Ordinary Differential Equations, which allows for transient, steady-state or bifurcation analysis when kinetic information is available. Complementary structure-related qualitative analysis techniques have become increasingly popular in rec... [more] Many models in Systems Biology are described as a system of Ordinary Differential Equations, which allows for transient, steady-state or bifurcation analysis when kinetic information is available. Complementary structure-related qualitative analysis techniques have become increasingly popular in recent years, like qualitative model checking or pathway analysis (elementary modes, invariants, flux balance analysis, graph-based analyses, chemical organization theory, etc.). They do not rely on kinetic information but require a well-defined structure as stochastic analysis techniques equally do. In this article, we look into the structure inference problem for a model described by a system of Ordinary Differential Equations and provide conditions for the uniqueness of its solution. We describe a method to extract a structured reaction network model, represented as a bipartite multigraph, for example, a continuous Petri net (CPN), from a system of Ordinary Differential Equations (ODEs). A CPN uniquely defines an ODE, and each ODE can be transformed into a CPN. However, it is not obvious under which conditions the transformation of an ODE into a CPN is unique, that is, when a given ODE defines exactly one CPN. We provide biochemically relevant sufficient conditions under which the derived structure is unique and counterexamples showing the necessity of each condition. Our method is implemented and available; we illustrate it on some signal transduction models from the BioModels database. A prototype implementation of the method is made available to modellers at http://contraintes.inria.fr/~soliman/ode2pn.html, and the data mentioned in the "Results" section at http://contraintes.inria.fr/~soliman/ode2pn_data/. Our results yield a new recommendation for the import/export feature of tools supporting the SBML exchange format.
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4.93Impact points
A general computational method for robustness analysis with applications to synthetic gene networks.
Bioinformatics (Oxford, England). 07/2009; 25(12):i169-78.
MOTIVATION: Robustness is the capacity of a system to maintain a function in the face of perturbations. It is essential for the correct functioning of natural and engineered biological systems. Robustness is generally defined in an ad hoc, problem-dependent manner, thus hampering the fruitful develo... [more] MOTIVATION: Robustness is the capacity of a system to maintain a function in the face of perturbations. It is essential for the correct functioning of natural and engineered biological systems. Robustness is generally defined in an ad hoc, problem-dependent manner, thus hampering the fruitful development of a theory of biological robustness, recently advocated by Kitano. RESULTS: In this article, we propose a general definition of robustness that applies to any biological function expressible in temporal logic LTL (linear temporal logic), and to broad model classes and perturbation types. Moreover, we propose a computational approach and an implementation in BIOCHAM 2.8 for the automated estimation of the robustness of a given behavior with respect to a given set of perturbations. The applicability and biological relevance of our approach is demonstrated by testing and improving the robustness of the timed behavior of a synthetic transcriptional cascade that could be used as a biological timer for synthetic biology applications. AVAILABILITY: Version 2.8 of BIOCHAM and the transcriptional cascade model are available at http://contraintes.inria.fr/BIOCHAM/.
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2.57Impact points
Dynamics of the interlocked positive feedback loops explaining the robust epigenetic switching in Candida albicans.
Journal of theoretical biology. 06/2009; 258(1):71-88.
The two element mutual activation and inhibitory positive feedback loops are a common motifs that occur in many biological systems in both isolated and interlocked form, as for example, in the cell division cycle and thymus differentiation in eukaryotes. The properties of three element interlocked p... [more] The two element mutual activation and inhibitory positive feedback loops are a common motifs that occur in many biological systems in both isolated and interlocked form, as for example, in the cell division cycle and thymus differentiation in eukaryotes. The properties of three element interlocked positive feedback loops that embeds both mutual activation and inhibition are studied in depth for their bistable properties by performing bifurcation and stochastic simulations. Codimension one and two bifurcations reveal important properties like robustness to parameter variations and adaptability under various conditions by its ability to fine tune the threshold to a wide range of values and to maintain a wide bistable regime. Furthermore, we show that in the interlocked circuit, mutual inhibition controls the decision to switch from OFF to ON state, while mutual activation enforces the decision. This view is supported through a concrete biological example Candida albicans, a human fungal pathogen that can exist in two distinctive cell types; one in the default white state and the other in an opaque form. Stochastic switching between these two forms takes place due to the epigenetic alternation induced by the transcriptional regulators in the circuit, albeit without any rearrangement of the nuclear chromosomes. The transcriptional regulators constitute interlocked mutual activation and inhibition feedback circuits that provide adaptable threshold and wide bistable regime. These positive feedback loops are shown to be responsible for robust noise induced transitions without chattering, persistence of particular phenotypes for many generations and selective exhibition of one particular form of phenotype when mutated. Finally, we propose for synthetic biology constructs to use interlocked positive feedback loops instead of two element positive feedback loops because they are better controlled than isolated mutual activation and mutual inhibition feedback circuits.
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On Coupling Models Using Model-Checking: Effects of Irinotecan Injections on the Mammalian Cell Cycle.
Computational Methods in Systems Biology, 7th International Conference, CMSB 2009, Bologna, Italy, August 31-September 1, 2009. Proceedings; 01/2009
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On a Continuous Degree of Satisfaction of Temporal Logic Formulae with Applications to Systems Biology.
Computational Methods in Systems Biology, 6th International Conference, CMSB 2008, Rostock, Germany, October 12-15, 2008. Proceedings; 01/2008
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Formal Cell Biology in Biocham.
Formal Methods for Computational Systems Biology, 8th International School on Formal Methods for the Design of Computer, Communication, and Software Systems, SFM 2008, Bertinoro, Italy, June 2-7, 2008, Advanced Lectures; 01/2008
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From Reaction Models to Influence Graphs and Back: A Theorem.
Formal Methods in Systems Biology, First International Workshop, FMSB 2008, Cambridge, UK, June 4-5, 2008. Proceedings; 01/2008
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Model Revision from Temporal Logic Properties in Computational Systems Biology.
Probabilistic Inductive Logic Programming - Theory and Applications; 01/2008
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Langages formels dans la machine abstraite biochimique BIOCHAM.
Technique et Science Informatiques. 01/2007; 26:47-72.
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Closures and Modules Within Linear Logic Concurrent Constraint Programming.
FSTTCS 2007: Foundations of Software Technology and Theoretical Computer Science, 27th International Conference, New Delhi, India, December 12-14, 2007, Proceedings; 01/2007
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4.93Impact points
BIOCHAM: an environment for modeling biological systems and formalizing experimental knowledge.
Bioinformatics (Oxford, England). 08/2006; 22(14):1805-7.
BIOCHAM (the BIOCHemical Abstract Machine) is a software environment for modeling biochemical systems. It is based on two aspects: (1) the analysis and simulation of boolean, kinetic and stochastic models and (2) the formalization of biological properties in temporal logic. BIOCHAM provides tools an... [more] BIOCHAM (the BIOCHemical Abstract Machine) is a software environment for modeling biochemical systems. It is based on two aspects: (1) the analysis and simulation of boolean, kinetic and stochastic models and (2) the formalization of biological properties in temporal logic. BIOCHAM provides tools and languages for describing protein networks with a simple and straightforward syntax, and for integrating biological properties into the model. It then becomes possible to analyze, query, verify and maintain the model with respect to those properties. For kinetic models, BIOCHAM can search for appropriate parameter values in order to reproduce a specific behavior observed in experiments and formalized in temporal logic. Coupled with other methods such as bifurcation diagrams, this search assists the modeler/biologist in the modeling process. AVAILABILITY: BIOCHAM (v. 2.5) is a free software available for download, with example models, at http://contraintes.inria.fr/BIOCHAM/.
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Type Inference in Systems Biology.
Computational Methods in Systems Biology, International Conference, CMSB 2006, Trento, Italy, October 18-19, 2006, Proceedings; 01/2006
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CLPGUI: a Generic Graphical User Interface for Constraint Logic Programming
08/2004;
CLPGUI is a generic graphical user interface for visualizing and controlling the execution of constraint logic programs. CLPGUI has been designed to be used in di#erent contexts: initially for teaching purposes, then for debugging complex programs of real-world scale, and recently for developing end... [more] CLPGUI is a generic graphical user interface for visualizing and controlling the execution of constraint logic programs. CLPGUI has been designed to be used in di#erent contexts: initially for teaching purposes, then for debugging complex programs of real-world scale, and recently for developing end-user interfaces. The challenge of developing a tool which is generic w.r.t. both the constraint logic programming system and the visualizers, is addressed by a client-server architecture for connecting a CLP process to a Java-based GUI process, and by a non-intrusive tracing and control method based on annotations in the CLP program. Arbitrary constraints and goals can be posted incrementally from the GUI in an interactive manner, and arbitrary states can be recomputed. We describe several generic 2D and 3D viewers of the variables and of the search tree, and argue that the 3D representation is best-suited to apprehend the shape of large search trees. We also illustrate the use of CLPGUI for developing application-oriented end-user interfaces on two placement problems, one in virtual reality.
Following (7)
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Marianna Limas
Universidade de São Paulo -
Monika Heiner
Brandenburgische Technische Universität Cottbus -
Laurence Calzone
Institut Curie - Research (Paris) -
David Gilbert
University of Surrey -
Mattias Villani
Linkoping University
