A knowledge representation meta-model for rule-based modelling of signalling networks

The study of cellular signalling pathways and their deregulation in disease states, such as cancer, is a large and extremely complex task. Indeed, these systems involve many parts and processes but are studied piecewise and their literatures and data are consequently fragmented, distributed and sometimes--at least apparently--inconsistent. This makes it extremely difficult to build significant explanatory models with the result that effects in these systems that are brought about by many interacting factors are poorly understood. The rule-based approach to modelling has shown some promise for the representation of the highly combinatorial systems typically found in signalling where many of the proteins are composed of multiple binding domains, capable of simultaneous interactions, and/or peptide motifs controlled by post-translational modifications. However, the rule-based approach requires highly detailed information about the precise conditions for each and every interaction which is rarely available from any one single source. Rather, these conditions must be painstakingly inferred and curated, by hand, from information contained in many papers--each of which contains only part of the story. In this paper, we introduce a graph-based meta-model, attuned to the representation of cellular signalling networks, which aims to ease this massive cognitive burden on the rule-based curation process. This meta-model is a generalization of that used by Kappa and BNGL which allows for the flexible representation of knowledge at various levels of granularity. In particular, it allows us to deal with information which has either too little, or too much, detail with respect to the strict rule-based meta-model. Our approach provides a basis for the gradual aggregation of fragmented biological knowledge extracted from the literature into an instance of the meta-model from which we can define an automated translation into executable Kappa programs.Comment: In Proceedings DCM 2015, arXiv:1603.0053

Gubs, un langage de description comportementale pour la biologie de synthèse: Conception d'un langage dédié à la conception de fonctions biologiques de synthèse par compilation de spécifications comportementales

The field of synthetic biology is looking forward engineering framework for safely designing reliable de-novo biological functions. In this undertaking, Computer-Aided-Design (CAD) environments should play a central role for facilitating the design. Although, CAD environment is widely used to engineer artificial systems the application in synthetic biology is still in its infancy. In this article we address the problem of the design of a high level language which at the core of CAD environment. More specifically the Gubs (Genomic Unified Behavioural Specification) language is a specification language used to describe the observations of the expected behaviour. The compiler appropriately selects components such that the observation of the synthetic biological function resulting to their assembly complies to the programmed behaviour.La biologie de synthèse est un domaine émergent en quête d’outils afin deformaliser et d’automatiser la caractérisation et la conception de systèmes biologiques.Dans ce cadre, nous proposons un langage de spécification comportementale dessystèmes biologiques, ainsi que la conception d’un compilateur traduisant cettespécification en un assemblage de composants biologiques.La première partie sera dédiée à un langage de description comportementalenommé Gubs (Genetic Unified Behaviour Specification) pour la spécification decomposants biologiques en les décrivant comme des systèmes ouverts dynamiques etdiscrets. Gubs est un langage déclaratif dont la syntaxe se fonde sur une descriptiondes comportements par un ensemble de relations causales. Contrairement à un systèmefermé, un programme est toujours une description partielle du comportement dusystème. La sémantique a été conçue afin de prendre en compte la présence d’actionsnon spécifiées qui pourraient potentiellement altérer le comportement des composantsprogrammés en l’exprimant sous forme d’une formule de logique hybride.En seconde partie, nous introduisons un système formel décrivant les principes decompilation d’une spécification en Gubs en un ensemble de composants biologiquessynthétisables. Ce système est implémenté par Ggc, un compilateur permettant desélectionner automatiquement les composants possédant les propriétés adéquatespour qu’une fois assemblés ils simulent le comportement décrit. La compilation d’unespécification Gubs s’appuie sur le principe d’ACI-Unification en utilisant un schémasimilaire au système de preuve automatique afin de sélectionner les composants dontl’assemblage est correct par rapport à la spécification. Dans le cadre d’une unificationavec une base de données de grande taille, l’algorithme d’ACI-Unification bascule surun algorithme évolutionnaire d’optimisation permettant la recherche des composantsen adéquation avec le programme afin d’obtenir une solution.Finalement, cette thèse se conclut sur un ensemble d’optimisations permettantde sélectionner des composants selon des propriétés biologiques afin d’obtenir unesélection plus fine dans le but d’assurer une synthèse des éléments in-silico en systèmesbiologiques viables in-vivo. Nous concluons aussi sur un traitement automatique desbases de données à disposition des chercheurs afin de les traduire en un ensemble decomposants Gubs

GUBS, a Behavior-based Language for Open System Dedicated to Synthetic Biology

In this article, we propose a domain specific language, GUBS (Genomic Unified Behavior Specification), dedicated to the behavioral specification of synthetic biological devices, viewed as discrete open dynamical systems. GUBS is a rule-based declarative language. By contrast to a closed system, a program is always a partial description of the behavior of the system. The semantics of the language accounts the existence of some hidden non-specified actions possibly altering the behavior of the programmed device. The compilation framework follows a scheme similar to automatic theorem proving, aiming at improving synthetic biological design safety.Comment: In Proceedings MeCBIC 2012, arXiv:1211.347

GUBS, a behaviour-based language for design in synthetic biology

International audienceIn this article, we propose a domain specific language, GUBS (Genomic Unified Behaviour Specification), dedicated to the behavioural specification of synthetic biological devices, viewed as discrete open dynamical systems. GUBS is a rule-based declarative language. In contrast to a closed system, a program is always a partial description of the behaviour of the system. The semantics of the language accounts the existence of some hidden non-specified actions that possibly alter the behaviour of the programmed devices. The compilation framework follows a scheme similar to automated theorem proving, aiming at improving synthetic biological design safety

Towards a Behavioral-Matching Based Compilation of Synthetic Biology Functions

International audienceThe field of synthetic biology is looking forward engineering framework for safely designing reliable de-novo biological functions. In this undertaking, Computer-Aided-Design (CAD) environments should play a central role for facilitating the design. Although, CAD environment is widely used to engineer artificial systems the application in synthetic biology is still in its infancy. In this article we address the problem of the design of a high level language which at the core of CAD environment. More specifically the Gubs (Genomic Unified Behavioural Specification) language is a specification language used to describe the observations of the expected behaviour. The compiler appropriately selects components such that the observation of the synthetic biological function resulting to their assembly complies to the programmed behaviour