Fundamenta Informaticae - Volume 160, issue 1-2

Authors: Gambin, Anna | Heiner, Monika

Article Type: Other

DOI: 10.3233/FI-2018-1671

Citation: Fundamenta Informaticae, vol. 160, no. 1-2, pp. v-vii, 2018

Authors: Fortin, Mathieu Pagé | Hardy, Simon V.

Article Type: Research Article

Abstract: Signalling networks in the mammalian cell are complex systems. Their dynamic properties can often be explained by the interaction of regulatory network motifs. Computational modelling is instrumental in explaining how these systems function. To accomplish this task in this paper, we combine hybrid Petri net modelling and simulation, which produce the individual trajectories of protein concentrations and enable structural analysis of the reaction network. In the end, we generate dynamic graphs to get a system view of the signalling network dynamics. We use this methodology on the regulatory network of the proteins mTOR and p70S6K. In neuronal synaptic plasticity, prolonged …activation of these proteins is needed to support an increased protein synthesis. However, biologists wonder how two brief calcium influxes of 1 second each can lead to this long activation downstream. With our computational approach and a new model of the Akt-Wnt-mTOR-p70S6K network, we explore the current biological hypothesis for the response of mTOR: the crosstalk between the Akt and Wnt pathways. Simulation results indicate instead that a feedforward motif between Akt, GSK3 and TSC2 acts as a coincidence detector. From the simulation results, we can also make two predictions that can be tested experimentally and indicate where a molecular regulatory mechanism seems to be missing to completely explain the activity in the signalling network. Show more

Keywords: Computational biology, Cell signalling, Hybrid Petri net modelling, Simulation, mTOR, Synaptic plasticity

DOI: 10.3233/FI-2018-1672

Citation: Fundamenta Informaticae, vol. 160, no. 1-2, pp. 1-25, 2018

Authors: Baldan, Paolo | Bocci, Martina | Brigolin, Daniele | Cocco, Nicoletta | Heiner, Monika | Simeoni, Marta

Article Type: Research Article

Abstract: We consider trophic networks, a kind of networks used in ecology to represent feeding interactions (what-eats-what) in an ecosystem. Starting from the observation that trophic networks can be naturally modelled as Petri nets, we explore the possibility of using Petri nets for the analysis and simulation of trophic networks. We define and discuss different continuous Petri net models, whose level of accuracy depends on the information available for the modelled trophic network. The simplest Petri net model we construct just relies on the topology of the network. We also propose a technique for deriving a more refined model that embeds …into the Petri net the known constraints on the transition rates that represent the knowledge on metabolism and diet of the species in the network. Finally, if the information of the biomass amounts for each species at steady state is available, we discuss a way of further refining the Petri net model in order to represent dynamic behaviour. We apply our Petri net technology to a case study of the Venice lagoon and analyse the results. Show more

DOI: 10.3233/FI-2018-1673

Citation: Fundamenta Informaticae, vol. 160, no. 1-2, pp. 27-52, 2018

Authors: Herajy, Mostafa | Heiner, Monika

Article Type: Research Article

Abstract: Continuous Petri nets (CPN) provide a graphical tool to model and analyse the deterministic dynamic behaviour of biological reaction networks. They can be considered as an alternative to the traditional ODE representation of biological models, enjoying a visual depiction of reaction networks. A model constructed as CPN can take advantages of quantitative (e.g., transient and steady state analysis) as well as qualitative (e.g., structural analysis) techniques. However, there are different semantics of CPN due to varying interpretations of transition rates. Choosing an appropriate semantics and corresponding simulator is not a straightforward procedure for the modelling of certain biological systems. In …this paper, we compare two widely used semantics of CPN: adaptive semantics and bio-semantics. In the adaptive case, the enabling of continuous transitions may vary and the ODEs are correspondingly adjusted during model execution in order to avoid negative markings, while continuous transitions are always enabled in the bio-semantics and ODEs are never altered during the whole simulation period. We discuss the implementation complexity of both approaches in the context of systems biology and present two case studies to illustrate the best utilisation and individual strength of the two interpretations. Show more

Keywords: Continuous Petri Nets, Adaptive semantics, Bio-semantics, Modelling Biological Networks, Deterministic Simulation, Liver Iron Metabolism

DOI: 10.3233/FI-2018-1674

Citation: Fundamenta Informaticae, vol. 160, no. 1-2, pp. 53-80, 2018

Authors: Bordon, Jure | Moškon, Miha | Zimic, Nikolaj | Mraz, Miha

Article Type: Research Article

Abstract: Petri nets are a well-established modelling framework in life sciences and have been widely applied to systems and synthetic biology in recent years. With the various extensions they serve as graphical and simulation interface for both qualitative and quantitative modelling approaches. In terms of quantitative approaches, Stochastic and Continuous Petri nets are extensively used for modelling biological system’s dynamics if underlying kinetic data are known. However, these are often only vaguely defined or even missing. In this paper we present a fuzzy approach, which can be used to model biological processes with unknown kinetic data in order to still obtain …quantitatively relevant simulation results. We define fuzzy firing rate functions, which can be used in Continuous Petri nets and are able to describe different processes that govern the dynamics of gene expression networks. They can be used in combination with the conventional firing rate functions and applied only in the parts of the system for which the kinetic data are missing. The case study of the proposed approach is performed on models of a hypothetical repressilator and Neurospora circadian rhythm. Show more

Keywords: Petri nets, modelling biological processes, fuzzy logic, unknown kinetic parameter values

DOI: 10.3233/FI-2018-1675

Citation: Fundamenta Informaticae, vol. 160, no. 1-2, pp. 81-100, 2018

Authors: Liu, Fei | Chen, Siyuan

Article Type: Research Article

Abstract: Fuzzy approaches play an important role in the modeling of genetic regulatory networks (GRNs) with incomplete quantitative data. However, current fuzzy approaches such as fuzzy logic and fuzzy Petri nets (FPNs) can neither clearly describe causal relationships between genes as each interaction between genes is represented by a couple of fuzzy rules, nor easily deal with large GRNs. To address these issues, this paper presents a new class of colored fuzzy Petri nets (CFPNs) by combining colored Petri nets with FPNs, which makes it possible to clearly represent interactions among genes or to construct a compact model for a large …GRN requiring many fuzzy rules. We give the definition of CFPNs and a simulation approach which incorporates a reasoning algorithm, as well as a detailed procedure for modeling and analyzing GRNs with CFPNs. We illustrate our approach using a simple example comprising six genes. Show more

Keywords: genetic regulatory networks, colored fuzzy Petri nets, fuzzy logic, simulation algorithm

DOI: 10.3233/FI-2018-1676

Citation: Fundamenta Informaticae, vol. 160, no. 1-2, pp. 101-118, 2018

Authors: Delaplace, Franck | Di Giusto, Cinzia | Giavitto, Jean-Louis | Klaudel, Hanna | Spicher, Antoine

Article Type: Research Article

Abstract: ANDy, Activity Networks with Delays, is a discrete framework aiming at the qualitative modeling of time-dependent activities. The modular and expressive syntax makes ANDy suitable for a concise and natural modeling of time-dependent biological systems (i.e ., regulatory pathways). Activities involve entities playing the role of activators, inhibitors or products of biochemical network operation. Activities may have a given duration, i.e ., the time required to obtain results. An entity may represent an object (e.g ., an agent, a biochemical species or a family of thereof) with a local attribute, a state denoting its level (e.g ., concentration, strength). …Entity levels may change as a result of an activity or may decay gradually as time passes by. The semantics of ANDy is formally given via high-level Petri nets ensuring this way some modularity. As main results we show that ANDy systems have finite state representations even for potentially infinite processes and it well adapts to the modeling of toxic behaviors. As an illustration, we present a classification of toxicity properties and give some hints on how they can be verified on ANDy systems with existing tools. A case study on blood glucose regulation is provided to exemplify the ANDy framework and the toxicity properties. Show more

Keywords: Petri nets, toxicity, reaction networks, model checking

DOI: 10.3233/FI-2018-1677

Citation: Fundamenta Informaticae, vol. 160, no. 1-2, pp. 119-142, 2018

Authors: Formanowicz, Dorota | Rybarczyk, Agnieszka | Formanowicz, Piotr

Article Type: Research Article

Abstract: Essential hypertension is the world’s most prevalent cardiovascular disorder, however, its etiology remains poorly understood, making it difficult to study. The evidence suggests that inflammation can lead to the development of hypertension and that oxidative stress and endothelial dysfunction are involved in the inflammatory cascade. In this work, to investigate the influence of these factors on the essential hypertension development, a stochastic Petri net model has been built and then analyzed. To obtain appropriate initial marking and kinetic rate constants for the model, a simple heuristic has been developed. The application of this variant of Petri nets allowed for taking …into account some important dependencies present in the modeled system what would be impossible in the case of qualitative models. This has enabled for an in-depth analysis of the studied phenomenon and a validation of biological conclusions previously obtained on the basis of a qualitative model. Show more

Keywords: hypertension, inflammation, stochastic Petri nets, simulation, knockout analysis

DOI: 10.3233/FI-2018-1678

Citation: Fundamenta Informaticae, vol. 160, no. 1-2, pp. 143-165, 2018

Authors: Bashirov, Rza | Akçay, Nimet İlke

Article Type: Research Article

Abstract: In this work we use hybrid Petri nets to create a model of the p16-mediated signaling pathway in higher eukaryotes and conduct its stochastic simulation-based validation by wet lab observations available from literature. The validation is conducted in terms of stochastic simulations with respect to the wild-type p16 protein and its mutated form. Our model catches the behavior of the major molecular regulators of the p16-mediated signaling pathway in wild-type cells as well as when DNA damage is detected or replicative senescence occurs. We observe that the stochastic model predicts some characteristics of the underlying pathway more clearly, evidently and …perspicuously compared to the deterministic model, enriching the breadth and the quality of the outcome. Show more

Keywords: Stochastic quantitative modeling, Snoopy, hybrid Petri net, p16-mediated signaling pathway

DOI: 10.3233/FI-2018-1679

Citation: Fundamenta Informaticae, vol. 160, no. 1-2, pp. 167-179, 2018

Authors: Rohr, Christian

Article Type: Research Article

Abstract: We present an approach to improve the efficiency of stochastic simulation for large and dense biochemical reaction networks. We use stochastic Petri nets as modelling framework, but the proposed simulation approach is not limited to Petri net representations. The underlying continuous-time Markov chain (CTMC) is converted to an equivalent discrete-time Markov chain (DTMC); this itself gains no efficiency. We improve the efficiency via discrete-time leaps, even though this results in an approximate method. The discrete-time leaps are done by applying the maximum firing rule; this reduces drastically the number of steps. The presented algorithm is implemented in our modelling and …simulation tool Snoopy, as well as in our advanced analysis and model checking tool MARCIE. We demonstrate the approach on models of different sizes and complexities. Show more

Keywords: discrete-time leap method, stochastic Petri net, approximate stochastic simulation, maximum firing rule, binomial distribution, weighted random shuffle

DOI: 10.3233/FI-2018-1680

Citation: Fundamenta Informaticae, vol. 160, no. 1-2, pp. 181-198, 2018

Authors: Grabowski, Marek | Bokota, Grzegorz | Sroka, Jacek | Kierzek, Andrzej

Article Type: Research Article

Abstract: We present a tool for the verification of qualitative biological models. These models formalise observed behaviours and interrelations of molecular and cellular mechanisms. During its development a model is continuously verified. Predicted behaviours are compared with behaviours observed in experimental data. Moreover, the model must not exhibit behaviours which contradict existing knowledge about capabilities of the biological system under investigation. Model development is an iterative process involving many rounds of prediction, verification and refinement. Due to the complexity of biological systems this process is laborious and error prone, which motivates the development of “model debugging” tools. The qualitative models …we investigate represent large-scale molecular interaction networks describing gene regulation, signalling and whole-cell metabolism. We integrate a steady state model of whole-cell metabolism with a dynamic model of gene regulation and signalling represented as a Petri net. This Quasi-Steady State Petri Net (QSSPN) representation allows the generation of dynamic sequences of molecular events satisfying substrate, activator, inhibitor and metabolic flux requirements at every state transition. The reachability graph of the dynamic part of the model is examined and for every transition in this graph the satisfaction of metabolic flux requirements is verified by well-established linear programming techniques. Our approach is based on network connectivity alone and does not require any kinetic parameters. We demonstrate the applicability of our method by analysing a large-scale model of a nuclear receptor network regulating bile acid homeostasis in human hepatocyte. To date, simulation and verification of QSSPN models have been performed exclusively by Monte Carlo simulation. Random walks through the state space were used to find examples of behaviour satisfying properties of interest. Here, we provide for the first time for QSSPN models an exhaustive analysis of the state space up to a finite depth, which is possible due to several effective optimisations. Contrary to the Monte Carlo approach, we can prove that certain behaviour cannot be realised by the model within a given number of steps. This allows rejection of models which are not capable to reproduce experimentally observed behaviours, as well as verification that biologically unrealistic behaviours cannot occur in the simulation. We show an example of how these features improve identification of problems in large scale network models. Show more

DOI: 10.3233/FI-2018-1681

Citation: Fundamenta Informaticae, vol. 160, no. 1-2, pp. 199-219, 2018

Authors: Blätke, Mary-Ann | Rohr, Christian

Article Type: Research Article

Abstract: Systems and synthetic biology require multiscale biomodel engineering approaches to integrate diverse spatial and temporal scales which will help to better understand and describe the various interactions in biological systems. Our BioModelKit framework for modular biomodel engineering allows composing multiscale models from a set of modules, each describing an individual biomolecular component in the form of a Petri net. In this framework, we now propose a feature for spatial modelling of molecular biosystems. The spatial model represents the coordinates and movement of individual biomolecular components on a defined grid. Here, the distance between components constrains their ability to interact with …each other. We use coloured Petri nets to scale the spatial model, such that each molecular component can exist in an arbitrary number of instances. The grid can encode various regular and irregular structures according to the cellular arrangement and geometry. Furthermore, the grid can be divided into compartments to represent the compartmentalisation of the cell. Show more

Keywords: modular model composition, spatial modelling, multiscale biomodel-engineering, coloured Petri nets

DOI: 10.3233/FI-2018-1682

Citation: Fundamenta Informaticae, vol. 160, no. 1-2, pp. 221-254, 2018