Sylvain Soliman

On the Trap Space Semantics of Normal Logic Programs

The logical semantics of normal logic programs has traditionally been based on the notions of Clark’s completion and two-valued or three-valued canonical models, including …

Van-Giang Trinh
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DigiDermA: Modeling Cellular and Molecular Interactions in Atopic Dermatitis

We analyzed publicly available single-cell RNA sequencing data (GEO accession GSE147424) derived from human skin biopsies of lesional and non-lesional atopic dermatitis samples …

Ouissem Saidi
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Graphical conditions for the existence, unicity and number of regular models

The regular models of a normal logic program are a particular type of partial (i.e. 3-valued) models which correspond to stable partial models with minimal undefinedness. In this …

Van-Giang Trinh
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On BIOCHAM Symbolic Computation Pipeline for Compiling Mathematical Functions into Biochemistry

Chemical Reaction Networks (CRNs) are a standard formalism used in chemistry and biology to model complex molecular interaction systems. In the perspective of systems biology, …

François Fages
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Scalable Enumeration of Trap Spaces in Boolean Networks via Answer Set Programming

Boolean Networks (BNs) are widely used as a modeling formalism in several domains, notably systems biology and computer science. A fundamental problem in BN analysis is the …

Giang Trinh
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MetaLo: metabolic analysis of Logical models extracted from molecular interaction maps

Molecular interaction maps (MIMs) are static graphical representations depicting complex biochemical networks that can be formalized using one of the Systems Biology Graphical …

Sahar Aghakhani
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Trap spaces of Boolean networks are conflict-free siphons of their Petri net encoding

Boolean network modeling of gene regulation but also of post-transcriptomic systems has proven over the years that it can bring powerful analyses and corresponding insight to the …

Van-Giang Trinh
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Hybrid computational modeling highlights reverse warburg effect in breast cancer-associated fibroblasts

Cancer-associated fibroblasts (CAFs) are amongst the key players of the tumor microenvironment (TME) and are involved in cancer initiation, progression, and resistance to therapy. …

Sahar Aghakhani
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Efficient Enumeration of Fixed Points in Complex Boolean Networks Using Answer Set Programming

Boolean Networks (BNs) are an efficient modeling formalism with applications in various research fields such as mathematics, computer science, and more recently systems biology. …

Van-Giang Trinh
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A large-scale Boolean model of the rheumatoid arthritis fibroblast-like synoviocytes predicts drug synergies in the arthritic joint

Abstract Rheumatoid arthritis (RA) is a complex autoimmune disease with an unknown aetiology. However, rheumatoid arthritis fibroblast-like synoviocytes (RA-FLS) play a …

Vidisha Singh
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Metabolic Reprogramming in Rheumatoid Arthritis Synovial Fibroblasts: a Hybrid Modeling Approach

Rheumatoid Arthritis (RA) is an autoimmune disease characterized by a highly invasive pannus formation consisting mainly of Synovial Fibroblasts (RASFs). This pannus leads to …

Sahar Aghakhani
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Minimal trap spaces of Logical models are maximal siphons of their Petri net encoding

Boolean modelling of gene regulation but also of post-transcriptomic systems has proven over the years that it can bring powerful analyses and corresponding insight to the many …

Van-Giang Trinh
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Symbolic Methods for Biological Networks D2.1 Report on Scalable Methods for Tropical Solutions (T1.2)

Tropical geometry can be used to find the order of time scales of variables in chemical reaction networks and search for model reductions [SGF+15]. In this report, we consider the …

Christoph Lüders
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Compiling Elementary Mathematical Functions into Finite Chemical Reaction Networks via a Polynomialization Algorithm for ODEs

The Turing completeness result for continuous chemical reaction networks (CRN) shows that any computable function over the real numbers can be computed by a CRN over a finite set …

Mathieu Hemery
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A Polynomialization Algorithm for Elementary Functions and ODEs, and their Compilation into Chemical Reaction Networks

In this short paper extracted from [7], we present a polynomialization algorithm of quadratic time complexity to transform a system of elementary differential equations in …

Mathieu Hemery
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On the Complexity of Quadratization for Polynomial Differential Equations

Chemical reaction networks (CRNs) are a standard formalism used in chemistry and biology to reason about the dynamics of molecular interaction networks. In their interpretation by …

Mathieu Hemery
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Graphical Conditions for Rate Independence in Chemical Reaction Networks

Chemical Reaction Networks (CRNs) provide a useful abstraction of molecular interaction networks in which molecular structures as well as mass conservation principles are …

Elisabeth Degrand
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On Inferring Reactions from Data Time Series by a Statistical Learning Greedy Heuristics

With the automation of biological experiments and the increase of quality of single cell data that can now be obtained by phospho-proteomic and time lapse videomicroscopy, …

Julien Martinelli
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A Statistical Unsupervised Learning Algorithm for Inferring Reaction Networks from Time Series Data

With the automation of biological experiments and the increase of quality of single cell data that can now be obtained by phosphoproteomic and time lapse videomicroscopy, …

Julien Martinelli
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Influence Networks compared with Reaction Networks: Semantics, Expressivity and Attractors

Biochemical reaction networks are one of the most widely used formalism in systems biology to describe the molecular mechanisms of high-level cell processes. However modellers …

François Fages
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