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Fundamenta Informaticae is an international journal publishing original research results in all areas of theoretical computer science. Papers are encouraged contributing:
- solutions by mathematical methods of problems emerging in computer science
- solutions of mathematical problems inspired by computer science.
Topics of interest include (but are not restricted to): theory of computing, complexity theory, algorithms and data structures, computational aspects of combinatorics and graph theory, programming language theory, theoretical aspects of programming languages, computer-aided verification, computer science logic, database theory, logic programming, automated deduction, formal languages and automata theory, concurrency and distributed computing, cryptography and security, theoretical issues in artificial intelligence, machine learning, pattern recognition, algorithmic game theory, bioinformatics and computational biology, quantum computing, probabilistic methods, & algebraic and categorical methods.
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
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