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1

Encoding Threshold Boolean Networks into Reaction Systems for the Analysis of Gene Regulatory Networks

Barbuti Roberto, Bove Pasquale, Gori Roberta, Gruska Damas, Levi Francesca, Milazzo Paolo

Fundamenta Informaticae

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2021

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Vol. 179, nr 2

205--225

EN

Gene regulatory networks represent the interactions among genes regulating the activation of specific cell functionalities and they have been successfully modeled using threshold Boolean networks. In this paper we propose a systematic translation of threshold Boolean networks into reaction systems. Our translation produces a non redundant set of rules with a minimal number of objects. This translation allows us to simulate the behavior of a Boolean network simply by executing the (closed) reaction system we obtain. This can be very useful for investigating the role of different genes simply by “playing” with the rules. We developed a tool able to systematically translate a threshold Boolean network into a reaction system. We use our tool to translate two well known Boolean networks modelling biological systems: the yeast-cell cycle and the SOS response in Escherichia coli. The resulting reaction systems can be used for investigating dynamic causalities among genes.

2

CospanSpan(Graph) : a Compositional Description of the Heart System

Gianola Alessandro, Kasangian Stefano, Manicardi Desiree, Sabadini Nicoletta, Schiavio Filippo, Tini Simone

Fundamenta Informaticae

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2020

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Vol. 171, nr 1-4

221--237

EN

In this paper, we recall the basic features of the CospanSpan(Graph) algebra for the compositional description of reconfigurable hierarchical networks. In particular, we focus on compositionality and on the possibility of describing the interactions among physical/biological systems, using a parallel with communication operation not considered in the usual Kleene’s algebra. As a novel application, we give a complete compositional description in Span(Graph) of a simplified version of the heart system.

3

Verification of Dynamic Behaviour in Qualitative Molecular Networks Describing Gene Regulation, Signalling and Whole-cell Metabolism

Grabowski M., Bokota G., Sroka J., Kierzek A.

Fundamenta Informaticae

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2018

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Vol. 160, nr 1/2

199--219

EN

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.

4

Preprocessing for Network Reconstruction : Feasibility Test and Handling Infeasibility

Wagler A. K., Wegener J.-T.

Fundamenta Informaticae

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2014

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Vol. 135, nr 4

521--535

EN

The context of this work is the reconstruction of Petri net models for biological systems from experimental data. Such methods aim at generating all network alternatives fitting the given data. For a successful reconstruction, the data need to satisfy two properties: reproducibility and monotonicity. In this paper, we focus on a necessary preprocessing step for a recent reconstruction approach. We test the data for reproducibility, provide a feasibility test to detect cases where the reconstruction from the given data may fail, and provide a strategy to cope with the infeasible cases. After having performed the preprocessing step, it is guaranteed that the (given or modified) data are appropriate as input for the main reconstruction algorithm.

5

Monitoring Changes in Dynamic Multiset Systems

Ciobanu G., Sburlan D.

Fundamenta Informaticae

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2014

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Vol. 134, nr 1/2

67--82

EN

Models of biological systems expressed as multiset rewriting systems can be very complex, impeding the analysis of their behaviour. In this paper we propose a practical solution to this problem, in the form of change monitors, i.e. computational instruments which synchronise with the model and record its behaviour. Change monitors play the role of passive observers. Since change monitors can automatically identify specific behaviours generated by the model under investigation, it is sufficient to focus only on the output produced by the monitors (instead of examining the dynamics of the initial model).

6

Describing Membrane Computations with a Chemical Calculus

Battyányi P., Vaszil G.

Fundamenta Informaticae

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2014

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Vol. 134, nr 1/2

39--50

EN

Membrane systems are nature motivated computational models inspired by certain basic features of biological cells and their membranes. They are examples of the chemical computational paradigm which describes computation in terms of chemical solutions where molecules interact according to rules defining their reaction capabilities. Chemical models can be presented by rewriting systems based on multiset manipulations, and they are usually given as a kind of chemical calculus which might also allow non-deterministic and non-sequential computations. Here we study membrane systems from the point of view of the chemical computing paradigm and show how computations of membrane systems can be described by such a chemical calculus.

7

A Petri net based model of oxidative stress in atherosclerosis

Formanowicz D., Kozak A., Formanowicz P.

Foundations of Computing and Decision Sciences

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2012

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Vol. 37, No. 2

59--78

EN

In this paper a Petri net based model of the process of oxidative stress in atherosclerosis is presented and analyzed. Model expressed in the language of Petri net theory have, on one hand, an intuitive graphical representation, and on the other hand their formal properties can be analyzed using rigorous mathematical methods. Moreover, the behavior of a net can be simulated what supports the process of model development and an interpretation of the results of the analysis. Both the analysis and the simulation can be supported by many freely available software tools. In the case of biological systems an analysis the t-invariants is especially important since they correspond to some elementary biological subprocesses. In this paper the results of such an analysis are presented. In particular, minimal t-invariants, MCT-sets and t-clusters are calculated, their biological meaning is determined and some biological conclusions are drawn.

8

Termodynamika nierównowagowa a inżynieria procesowa

Sieniutycz S.

Inżynieria Chemiczna i Procesowa

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2001

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T. 22, z. 3A

111--124

PL

Przedstawiono zarys teorii i zastosowań termodynamiki nierównowagowej, istotnych dla techniki procesowej. Naświetlono znaczenie dyscypliny, związek z inżynierią procesową, główne reprezentacje i kierunki teorii oraz zasadnicze wyniki. Rozważono zastosowania w układach fizykochemicznych i biologicznych: optymalnie sterowane operacje jednostkowe, procesy w maszynach cieplnych, nieliniowy ruch ciepła, zjawiska relaksacyjne i samo-propagujące fronty reakcyjno-dyfuzyjne. Podkreślono własność ekstremalnego zachowanie się układu termodynamicznego w obecności ograniczeń, która prowadzi do równań kinetycznych, praw zachowania i optymalnych parametrów (zasady wariacyjne i optymalizacja). Omówiono także perspektywy dyscypliny i wyzwania na przyszłość.

EN

The paper outlines the theory and applications of nonequilibrium thermodynamics essential in chemical engineering. We focus on the significance of the discipline, its link with the process engineering, main representations and directions of the theory, and basic results. Applications in physiochemical and biological systems are considered which involve: optimally controlled unit operations, processes in thermal machines, nonlinear heat transfer, relaxation phenomena and self-propagating reaction-diffusion fronts. We stress the property of extremum behaviour of the thermodynamic system in presence of constraints, which leads to kinetic equations, conservation laws and optimal parameters (variational principles and optimization). Discussed are also perspectives of the discipline and its future challenges.