Formal Modeling and Analysis of the MAL-Associated Biological Regulatory Network: Insight into Cerebral Malaria

The discrete modeling formalism of René Thomas is a well known approach for the modeling and analysis of Biological Regulatory Networks (BRNs). This formalism uses a set of parameters which reflect the dynamics of the BRN under study. These parameters are initially unknown but may be deduced from the appropriately chosen observed dynamics of a BRN. The discrete model can be further enriched by using the model checking tool HyTech along with delay parameters. This paves the way to accurately analyse a BRN and to make predictions about critical trajectories which lead to a normal or diseased response. In this paper, we apply the formal discrete and hybrid (discrete and continuous) modeling approaches to characterize behavior of the BRN associated with MyD88-adapter-like (MAL) – a key protein involved with innate immune response to infections. In order to demonstrate the practical effectiveness of our current work, different trajectories and corresponding conditions that may lead to the development of cerebral malaria (CM) are identified. Our results suggest that the system converges towards hyperinflammation if Bruton's tyrosine kinase (BTK) remains constitutively active along with pre-existing high cytokine levels which may play an important role in CM pathogenesis

Identification of Biological Regulatory Networks from Process Hitting models

International audienceQualitative formalisms offer a well-established alternative to the more tradi-tionally used differential equation models of Biological Regulatory Networks (BRNs). These formalisms led to numerous theoretical works and practical tools to understand emerging behaviors. The analysis of the dynamics of very large models is however a rather hard problem, which led us to previously in-troduce the Process Hitting framework (PH), which is a particular class of non-deterministic asynchronous automata network (or safe Petri nets). Its major advantage lies in the efficiency of several static analyses recently designed to assess dynamical properties, making it possible to tackle very large models. In this paper, we address the formal identification of qualitative models of BRNs from PH models. First, the inference of the Interaction Graph from a PH model summarizes the signed influences between the components that are effective for the dynamics. Second, we provide the inference of all René-Thomas models of BRNs that are compatible with a given PH. As the PH allows the specification of nondeterministic interactions between components, our inference emphasizes the ability of PH to deal with large BRNs with incomplete knowledge on interactions, where Thomas's approach fails because of the combinatorics of parameters. The inference of corresponding Thomas models is implemented using An-swer Set Programming, which allows in particular an efficient enumeration of (possibly numerous) compatible parametrizations

Incorporating Time Delays in Process Hitting Framework for Dynamical Modeling of Large Biological Regulatory Networks

Modeling and simulation of molecular systems helps in understanding the behavioral mechanism of biological regulation. Time delays in production and degradation of expressions are important parameters in biological regulation. Constraints on time delays provide insight into the dynamical behavior of a Biological Regulatory Network (BRN). A recently introduced Process Hitting (PH) Framework has been found efficient in static analysis of large BRNs, however, it lacks the inference of time delays and thus determination of their constraints associated with the evolution of the expression levels of biological entities of BRN is not possible. In this paper we propose a Hybrid Process Hitting scheme for introducing time delays in Process Hitting Framework for dynamical modeling and analysis of Large Biological Regulatory Networks. It provides valuable insights into the time delays corresponding to the changes in the expression levels of biological entities thus possibly helping in identification of therapeutic targets. The proposed framework is applied to a well-known BRNs of Bacteriophage λ and ERBB Receptor-regulated G1/S transition involved in the breast cancer to demonstrate the viability of our approach. Using the proposed approach, we are able to perform goal-oriented reduction of the BRN and also determine the constraints on time delays characterizing the evolution (dynamics) of the reduced BRN

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

Semantics of Biological Regulatory Networks

International audienceThe aim of the paper is to revisit the model of Biological Regulatory Networks (BRN) which was proposed by René Thomas to model the interactions between a set of genes. We give a formal semantics for BRN in terms of transition systems which formalizes the evolution rules given by René Thomas. Then we show how to use this model to find interesting properties of a BRN like the set of stable states, cycles etc using tools for analyzing transition systems