Analyzing Large Network Dynamics with Process Hitting

Paulevé, Loı̈c; Chancellor, Courtney; Folschette, Maxime; Magnin, Morgan; Roux, Olivier

doi:10.1002/9781119005223.ch4

Cited by 12 publications

(10 citation statements)

References 27 publications

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“…The dynamics of qualitative models is coarser than the one of the quantitative models, but it helps the tractability of the analysis of attractors, that are the final states of the system, and reachability properties while abstracting away kinetic parameters. On medium-size models, the computation of the exhaustive dynamics is possible, whereas methods to handle large-size qualitative models are emerging [ 30 – 32 ].…”

Section: Introductionmentioning

confidence: 99%

Qualitative dynamics semantics for SBGN process description

et al. 2016

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BackgroundQualitative dynamics semantics provide a coarse-grain modeling of networks dynamics by abstracting away kinetic parameters. They allow to capture general features of systems dynamics, such as attractors or reachability properties, for which scalable analyses exist. The Systems Biology Graphical Notation Process Description language (SBGN-PD) has become a standard to represent reaction networks. However, no qualitative dynamics semantics taking into account all the main features available in SBGN-PD had been proposed so far.ResultsWe propose two qualitative dynamics semantics for SBGN-PD reaction networks, namely the general semantics and the stories semantics, that we formalize using asynchronous automata networks. While the general semantics extends standard Boolean semantics of reaction networks by taking into account all the main features of SBGN-PD, the stories semantics allows to model several molecules of a network by a unique variable. The obtained qualitative models can be checked against dynamical properties and therefore validated with respect to biological knowledge. We apply our framework to reason on the qualitative dynamics of a large network (more than 200 nodes) modeling the regulation of the cell cycle by RB/E2F.ConclusionThe proposed semantics provide a direct formalization of SBGN-PD networks in dynamical qualitative models that can be further analyzed using standard tools for discrete models. The dynamics in stories semantics have a lower dimension than the general one and prune multiple behaviors (which can be considered as spurious) by enforcing the mutual exclusiveness between the activity of different nodes of a same story. Overall, the qualitative semantics for SBGN-PD allow to capture efficiently important dynamical features of reaction network models and can be exploited to further refine them.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-016-0285-0) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

Qualitative dynamics semantics for SBGN process description

et al. 2016

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“…Such a case occurs notably when the PH encodes the union of several Boolean or discrete networks, as described in [15,32].…”

Section: Parametrization Inferencementioning

confidence: 99%

Identification of biological regulatory networks from Process Hitting models

Folschette

Paulevé

Inoue

et al. 2015

Theoretical Computer Science

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Qualitative formalisms offer a well-established alternative to the more traditionally 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 introduce the Process Hitting framework (PH), which is a particular class of nondeterministic 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' approach fails because of the combinatorics of parameters. The inference of corresponding Thomas models is implemented using Answer Set Programming, which allows in particular an efficient enumeration of (possibly numerous) compatible parameterizations.

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“…This work utilizes a highly scalable analytical framework of Process Hitting (PH) already established for the static analysis of large scale BRNs. Process Hitting approach [9][23] [24] approach can analyze properties of very large scale biological regulatory networks of up to 10,000 biological entities [25][26] without constructing their state graph. This approach is capable of handling the networks of thousands of genes.…”

Section: Introductionmentioning

confidence: 99%

A Static Analysis ofWnt/β-Catenin andWnt/Ca²⁺Biological Regulatory Networks for ARVC Using Automata Network Model

et al. 2021

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The Wnt-activated β-catenin and Ca 2+ ions play a critical role in the regulation of physiology of cardiomyocytes. The dysregulation of both the components causes the replacement of myocardial mass right ventricle with fibrous and adipose tissue which results in the condition of Arrhythmogenic Right ventricular Cardiomyopathy (ARVC). The major hurdle in ARVC treatment is lack of effective therapies targeting the underlying root molecular biomarkers of pathogenesis. Despite major advancements in interpreting the mechanism of ARVC etiology, the dynamics of molecular links in underlying biological machinery are still being delineated. Previously, formal methods based computational modeling techniques including kinetic logic, Petri Nets, hybrid automata and static analysis have greatly contributed in increasing our comprehension to decipher the molecular systems dynamics. It has allowed the identification of biomarkers which can be utilized for target-based therapies owing to meticulous biological abstractions along with implementing reference map that confines together the discrete biological insights. In this study, we have performed the static analysis of the Biological Regulatory Networks (BRNs) of the Wnt/β-catenin and Wnt/Ca 2+ signaling pathways to identify the significant biomarkers for ARVC. The abstracted qualitative models of afore mentioned BRNs are first constructed in GINsim software tool and then these models are converted into Automata Network (ANs) Models using Pint software tool. The fix point analysis is performed which contributed in pinpointing the possible therapeutic strategies for ARVC treatment by identification of drug targets such as Gsk3, Ck1 and Axin in Wnt/β-catenin AN and Bak & Bax, Parp, mCalpain, JNk and CIn in Wnt/Ca 2+ AN. Moreover, the Bcl2 gene is identified as novel therapeutic remedy in both the ANs of ARVC. The Bcl2 gene prevents the cardiac apoptosis via positive regulation of Wnt in Wnt/β-catenin AN and through inhibition of Bak & Bax (apoptotic component) in Wnt/Ca 2+ AN.The current study tends to fulfill the scientific gap between wet lab studies and provides cost effective and time saving computational strategies for an effectual treatment for deadly diseases like ARVC.

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Analyzing Large Network Dynamics with Process Hitting

Cited by 12 publications

References 27 publications

Qualitative dynamics semantics for SBGN process description

Qualitative dynamics semantics for SBGN process description

Identification of biological regulatory networks from Process Hitting models

A Static Analysis ofWnt/β-Catenin andWnt/Ca²⁺Biological Regulatory Networks for ARVC Using Automata Network Model

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Analyzing Large Network Dynamics with Process Hitting

Cited by 12 publications

References 27 publications

Qualitative dynamics semantics for SBGN process description

Qualitative dynamics semantics for SBGN process description

Identification of biological regulatory networks from Process Hitting models

A Static Analysis ofWnt/β-Catenin andWnt/Ca2+Biological Regulatory Networks for ARVC Using Automata Network Model

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Product

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A Static Analysis ofWnt/β-Catenin andWnt/Ca²⁺Biological Regulatory Networks for ARVC Using Automata Network Model