scholarly journals Simulating reversible computation with reaction systems

2020 ◽  
Vol 2 (3) ◽  
pp. 179-193
Author(s):  
Attila Bagossy ◽  
György Vaszil
Keyword(s):  
Environmental Control ◽  
Formal Model ◽  
Living Cells ◽  
Reversible Reaction ◽  
Reversible Systems ◽  
Biochemical Reactions ◽  
Reversible Computation ◽  
Reaction Systems ◽  
Model Of Computation

Abstract Reaction systems are a formal model of computation providing a framework for investigating biochemical reactions inside living cells. We look at the functioning of these systems as a process producing a series of different possible sets of entities representing states which can be changed by the application of reactions, and we study reversibility and its simulation in this framework. Our goal is to establish an Undo-Redo-Do-like semantics of reversibility with environmental control over the direction of the computation following a so-called no-memory approach, that is, without introducing modifications to the model of reaction systems itself. We first establish requirements the systems must satisfy in order to produce processes consisting of states with unique predecessors, then define reversible reaction systems in terms of reversible interactive processes. For such reversible systems, we also construct simulator systems that can traverse between the states of reversible interactive processes back and forth based on the input of a special “rollback” symbol from the environment.

scholarly journals Facilitation in reaction systems

2020 ◽  
Vol 2 (3) ◽  
pp. 149-161
Author(s):  
Luca Manzoni ◽  
Antonio E. Porreca ◽  
Grzegorz Rozenberg
Keyword(s):  
Structural Properties ◽  
Living Cell ◽  
Formal Model ◽  
Biochemical Reactions ◽  
Reaction Systems ◽  
Model Of Computation ◽  
Dependency Graphs ◽  
Transition Graphs

Abstract Reaction systems is a formal model of computation which originated as a model of interactions between biochemical reactions in the living cell. These interactions are based on two mechanisms, facilitation and inhibition, and this is well reflected in the formulation of reaction systems. In this paper, we investigate the facilitation aspect of reaction systems, where the products of a reaction may facilitate other reactions by providing some of their reactants. This aspect is formalized through positive dependency graphs which depict explicitly such facilitating interactions. The focus of the paper is on demonstrating how structural properties of reaction systems defined through the properties of their positive dependency graphs influence the behavioural properties of (suitable subclasses of) reaction systems, which, as usual, are defined through their transition graphs.

FUNCTIONS DEFINED BY REACTION SYSTEMS

2011 ◽  
Vol 22 (01) ◽  
pp. 167-178 ◽  
Author(s):  
ANDRZEJ EHRENFEUCHT ◽  
MICHAEL MAIN ◽  
GRZEGORZ ROZENBERG
Keyword(s):  
Formal Model ◽  
A Priori ◽  
Reaction System ◽  
Transition Function ◽  
Complex Behavior ◽  
Biochemical Reactions ◽  
Reaction Systems ◽  
Available Resources

Reaction systems are a formal model of interactions between biochemical reactions. They consist of sets of reactions, where each reaction is classified by its set of reactants (needed for the reaction to take place), its set of inhibitors (each of which prevents the reaction from taking place), and its set of products (produced when the reaction takes place) – the set of reactants and inhibitors form the resources of the reaction. Each reaction system defines a (transition) function on its set of states. (States here are subsets of an a priori given set of biochemical entities.) In this paper we investigate properties of functions defined by reaction systems. In particular, we investigate how the power of defining functions depends on available resources, and we demonstrate that with small resources one can define functions exhibiting complex behavior.

SIMPLE REACTION SYSTEMS AND THEIR CLASSIFICATION

2014 ◽  
Vol 25 (04) ◽  
pp. 441-457 ◽  
Author(s):  
LUCA MANZONI ◽  
DIOGO POÇAS ◽  
ANTONIO E. PORRECA
Keyword(s):  
Equivalence Relation ◽  
Biochemical Reactions ◽  
Reaction Systems ◽  
Model Of Computation ◽  
Simple Reaction ◽  
Boolean Lattices

Reaction systems are a model of computation inspired by biochemical reactions involving reactants, inhibitors and products from a finite background set. We define a notion of multi-step simulation among reaction systems and derive a classification with respect to the amount of resources (reactants and inhibitors) involved in each reaction. We prove that “simple” reaction systems, having at most one reactant and one inhibitor per reaction, suffice in order to simulate arbitrary systems. Finally, we show that the equivalence relation of mutual simulation induces exactly five linearly ordered classes of reaction systems characterizing well-known subclasses of the functions over Boolean lattices, such as the constant, additive (join-semilattice endomorphisms), monotone, and antitone functions.

A TOUR OF REACTION SYSTEMS

2011 ◽  
Vol 22 (07) ◽  
pp. 1499-1517 ◽  
Author(s):  
ROBERT BRIJDER ◽  
ANDRZEJ EHRENFEUCHT ◽  
MICHAEL MAIN ◽  
GRZEGORZ ROZENBERG
Keyword(s):  
Biochemical Reactions ◽  
Transition Systems ◽  
Reaction Systems ◽  
Binary Counter ◽  
Research Themes ◽  
Formal Framework

Reaction systems are a formal framework for investigating processes carried out by biochemical reactions. This paper is an introduction to reaction systems. It provides basic notions together with the underlying intuition and motivation as well as two examples (a binary counter and transition systems) of "programming" with reaction systems. It also provides a tour of some research themes.

scholarly journals Single-Cell Biochemical Multiplexing by Multidimensional Phasor Demixing and Spectral Fluorescence Lifetime Imaging Microscopy

2021 ◽  
Vol 9 ◽  
Author(s):  
Kalina T. Haas ◽  
Maximilian W. Fries ◽  
Ashok R. Venkitaraman ◽  
Alessandro Esposito
Keyword(s):  
Fluorescence Lifetime ◽  
Cell Function ◽  
Resonance Energy Transfer ◽  
Resonance Energy ◽  
Living Cells ◽  
Fluorescence Lifetime Imaging ◽  
Biochemical Reactions ◽  
Lifetime Imaging ◽  
Spectrally Resolved ◽  
Single Living Cells

Revealing mechanisms underpinning cell function requires understanding the relationship between different biochemical reactions in living cells. However, our capabilities to monitor more than two biochemical reactions in living cells are limited. Therefore, the development of methods for real-time biochemical multiplexing is of fundamental importance. Here, we show that data acquired with multicolor (mcFLIM) or spectrally resolved (sFLIM) fluorescence lifetime imaging can be conveniently described with multidimensional phasor transforms. We demonstrate a computational framework capable of demixing three Forster resonance energy transfer (FRET) probes and quantifying multiplexed biochemical activities in single living cells. We provide a comparison between mcFLIM and sFLIM suggesting that sFLIM might be advantageous for the future development of heavily multiplexed assays. However, mcFLIM—more readily available with commercial systems—can be applied for the concomitant monitoring of three enzymes in living cells without significant losses.

scholarly journals Exponentially Fitted Two-Derivative Runge-Kutta Methods for Simulation of Oscillatory Genetic Regulatory Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Zhaoxia Chen ◽  
Juan Li ◽  
Ruqiang Zhang ◽  
Xiong You
Keyword(s):  
Living Cells ◽  
General Purpose ◽  
Exponential Fitting ◽  
Circadian Oscillation ◽  
Reaction Systems ◽  
Chemical Reaction Systems ◽  
Regulatory Systems ◽  
Special Character ◽  
Best Fitting ◽  
Exponentially Fitted

Oscillation is one of the most important phenomena in the chemical reaction systems in living cells. The general purpose simulation algorithms fail to take into account this special character and produce unsatisfying results. In order to enhance the accuracy of the integrator, the second-order derivative is incorporated in the scheme. The oscillatory feature of the solution is captured by the integrators with an exponential fitting property. Three practical exponentially fitted TDRK (EFTDRK) methods are derived. To test the effectiveness of the new EFTDRK methods, the two-gene system with cross-regulation and the circadian oscillation of the period protein inDrosophilaare simulated. Each EFTDRK method has the best fitting frequency which minimizes the global error. The numerical results show that the new EFTDRK methods are more accurate and more efficient than their prototype TDRK methods or RK methods of the same order and the traditional exponentially fitted RK method in the literature.

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