=Paper=
{{Paper
|id=Vol-2651/posterextabs2
|storemode=property
|title=Quantitative Reaction Systems
|pdfUrl=https://ceur-ws.org/Vol-2651/posterextabs2.pdf
|volume=Vol-2651
|authors=Wen Zeng,Vasileios Germanos
|dblpUrl=https://dblp.org/rec/conf/apn/ZengG20
}}
==Quantitative Reaction Systems==
https://ceur-ws.org/Vol-2651/posterextabs2.pdf
Quantitative Reaction Systems?
Wen Zeng and Vasileios Germanos
Cyber Technology Institute, School of Computer Science and Informatics
De Montfort University, Leicester LE1 9BH, U.K.
{wen.zeng.wz, vasileios.germanos}@gmail.com
Natural computing is a research area that investigates both human designed
computing inspired by nature and computing taking place in nature [4, 3]. The
former research strand examines models and computational techniques inspired
by nature, the latter examines, in terms of information processing, phenomena
taking place in nature [4, 3].
Examples of the first strand of research include evolutionary computation
with paradigms inspired by Darwinian evolution of spices, neural computation
with paradigms inspired by the functioning of the brain, quantum computation
with paradigms inspired by quantum mechanics, and molecular computation
with paradigms inspired by molecular biology [4, 3].
Examples of the second strand of research are investigations into the com-
putational nature of self-assembly, the computational nature of developmen-
tal processes, the computational nature of brain processes, the systems biology
approach to bio-networks where cellular processes are investigated in terms of
communication and interaction, and the computational nature of biochemical
reactions [4, 3]. The second strand of research highlights the fact that computer
science is the central science of information processing as well, and as such a
basic science for other scientific disciplines such as biology [4, 3].
This research is focusing on the formal frameworks for the investigation of
the functioning of the living cell. It belongs to the second strand of research, as
it looks at the functioning of the living cell in terms of formal processes result-
ing from interactions between biochemical reactions occurring in it. This study
considers that these interactions are caused by two mechanisms: facilitation and
inhibition – the reactions may facilitate or inhibit each other.
A reaction model is based on principles notably different from those underly-
ing other models of computation in computer science [4, 3, 5, 2]. The fundamental
idea of this framework is that the functioning of a living cell is based on inter-
actions between individual reactions [4, 3, 5, 2]. These interactions determine the
dynamic processes taking place in living cells, and reaction systems are an ab-
stract model of these processes [4, 3, 5, 2].
Typical examples of reaction systems in practice would be analysing user and
adversary behaviours in the organizations; analysing data security and privacy
in dynamic environments; a hardware system which suffers component break-
downs and reconfiguration; a distributed system whose software is continually
updated. Such diverse event-based systems all suffer from a very high dynamic
?
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mons License Attribution 4.0 International (CC BY 4.0).
Quantitative Reaction Systems 217
behaviour due to the intricate dependencies in the representation of the state
information, and dynamic system reconfiguration.
There exists some key methods to analyse the reaction systems: In [2], the
authors investigated which entities in the system are actually relevant from the
point of view of generating dynamic processes through such state transforma-
tions. In [5], the authors proposed Petri nets could be used to provide faithful se-
mantics of reaction systems, because Petri nets are a general and well-established
model of concurrent and distributed computation and behaviour, including that
taking place in biological system. In [1], the probabilistic behaviour of reaction
systems is considered. The authors represent sets of reactions by trees, they ob-
tain a useful tool to investigate the state spaces of reaction systems. This study
only can be treated as an initial step, and we will consider the extension and
application of this studies.
In our study, we consider the number of molecules of reaction systems which
allowing for quantitative modelling, and we investigate the interactive processes
in the reaction system. Functions and algorithms are introduced to analyse the
basic properties of such system.
Our work is inspired by Professor Grzegorz Rozenberg who delivered a work-
shop on reaction systems when we were post-doctorial research associates in
Newcastle University. We would like to thank Professor Maciej Koutny for his
vision, insight and detailed explanations about the entities in the system.
References
1. Brijder, R., Ehrenfeucht, A., Rozenberg, G.: Representing reaction systems by trees.
In: Computation, Physics and Beyond - International Workshop on Theoretical
Computer Science, WTCS 2012, Dedicated to Cristian S. Calude on the Occasion of
His 60th Birthday, Auckland, New Zealand, February 21-24, 2012, Revised Selected
and Invited Papers. pp. 330–342 (2012)
2. Ehrenfeucht, A., Kleijn, J., Koutny, M., Rozenberg, G.: Relevance of entities in
reaction systems. In: Languages Alive - Essays Dedicated to Jürgen Dassow on the
Occasion of His 65th Birthday. pp. 44–55 (2012)
3. Ehrenfeucht, A., Rozenberg, G.: Biochemical reactions as computations. In: Compu-
tation and Logic in the Real World, Third Conference on Computability in Europe,
CiE 2007, Siena, Italy, June 18-23, 2007, Proceedings. pp. 672–673 (2007)
4. Ehrenfeucht, A., Rozenberg, G.: Reaction systems. Fundam. Inform. 75(1-4), 263–
280 (2007)
5. Kleijn, J., Koutny, M., Rozenberg, G.: Petri nets for biologically motivated comput-
ing. Sci. Ann. Comp. Sci. 21(2), 199–225 (2011)