Chemical computing based on Turing patterns in two coupled cells with equal transport coefficients

Muzika, František; Schreiberová, Lenka; Schreiber, Igor

doi:10.1039/c4ra08859j

Cited by 12 publications

(20 citation statements)

References 65 publications

(72 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The networks of chemical oscillators can be formed in different ways. One can use individual continuously stirred chemical reactors (CSTRs) and link them by pumps ensuring the flow of reagents [ 29 , 30 ]. Alternatively, networks of oscillators can be formed by touching droplets containing a water solution of reagents of an oscillatory BZ reaction stabilized by lipids dissolved in the surrounding oil phase.…”

Section: Resultsmentioning

confidence: 99%

Applications of Information Theory Methods for Evolutionary Optimization of Chemical Computers

Górecki

2020

Entropy

View full text Add to dashboard Cite

It is commonly believed that information processing in living organisms is based on chemical reactions. However, the human achievements in constructing chemical information processing devices demonstrate that it is difficult to design such devices using the bottom-up strategy. Here I discuss the alternative top-down design of a network of chemical oscillators that performs a selected computing task. As an example, I consider a simple network of interacting chemical oscillators that operates as a comparator of two real numbers. The information on which of the two numbers is larger is coded in the number of excitations observed on oscillators forming the network. The parameters of the network are optimized to perform this function with the maximum accuracy. I discuss how information theory methods can be applied to obtain the optimum computing structure.

show abstract

Section: Resultsmentioning

confidence: 99%

Applications of Information Theory Methods for Evolutionary Optimization of Chemical Computers

Górecki

2020

Entropy

View full text Add to dashboard Cite

show abstract

“…In our previous work, an array of two coupled cells (Muzika et al, 2014) and a linear array of three coupled cells (Muzika and Schreiber, 2013) were described through bifurcation diagrams in the parameter plane of σ M and σ inh and in the parameter plane of σ inh and k ADP at fixed q. In the following we use the same parameter planes.…”

Section: Stability and Bifurcation Analysis Bifurcation Scenariosmentioning

confidence: 99%

“…Following these findings, in our previous work we examined the case of equal transport rate coefficients of activator and inhibitor using a core model of (Goldbeter and Moran, 1984) glycolysis as an oscillatory reaction. We identified coexisting discrete Turing patterns in linear arrays of two and three coupled cells (Muzika and Schreiber, 2013;Muzika et al, 2014) and applied targeted perturbations to perform basic logical functions. In our experimental research, we substituted membrane by a reciprocal peristaltic pumping to form a cyclic array of four coupled subsystems where the reaction of yeast extract and Dglucose took place (Muzika et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Advanced Chemical Computing Using Discrete Turing Patterns in Arrays of Coupled Cells

2020

Self Cite

View full text Add to dashboard Cite

We examine dynamical switching among discrete Turing patterns that enable chemical computing performed by mass-coupled reaction cells arranged as arrays with various topological configurations: three coupled cells in a cyclic array, four coupled cells in a linear array, four coupled cells in a cyclic array, and four coupled cells in a branched array. Each cell is operating as a continuous stirred tank reactor, within which the glycolytic reaction takes place, represented by a skeleton inhibitor-activator model where ADP plays the role of activator and ATP is the inhibitor. The mass coupling between cells is assumed to be operating in three possible transport regimes: (i) equal transport coefficients of the inhibitor and activator (ii) slightly faster transport of the activator, and (iii) strongly faster transport of the inhibitor. Each cellular array is characterized by two pairs of tunable parameters, the rate coefficients of the autocatalytic and inhibitory steps, and the transport coefficients of the coupling. Using stability and bifurcation analysis we identified conditions for occurrence of discrete Turing patterns associated with non-uniform stationary states. We found stable symmetric and/or asymmetric discrete Turing patterns coexisting with stable uniform periodic oscillations. To switch from one of the coexisting stable regimes to another we use carefully targeted perturbations, which allows us to build systems of logic gates specific to each topological type of the array, which in turn enables to perform advanced modes of chemical computing. By combining chemical computing techniques in the arrays with glycolytic excitable channels, we propose a cellular assemblage design for advanced chemical computing.

show abstract

“…A possibilidade de processamento de informações como o reconhecimento de padrões via memória associativa, [111][112][113] e operações computacionais através de portões lógicos simples, [114][115][116][117] tem atraído a atenção da comunidade científica para o desenvolvimento da computação química. A inovação tecnológica na confecção de processadores químicos pode impulsionar uma vertente alternativa eficiente no desenvolvimento de processadores em meios não-convencionais além de permitir um estudo mais profundo da relação entre a distribuição espacial dos padrões com o processamento de informações em sistemas biológicos complexos, como o cérebro.…”

Section: Futuras Direçõesunclassified

Turing Patterns in Chemical Systems

Nagao¹,

Varela²

2016

Química Nova

View full text Add to dashboard Cite

publicado na web em 18/02/2016 TURING PATTERNS IN CHEMICAL SYSTEMS. Spontaneous pattern formation in reaction-diffusion systems was theoretically proposed by Alan M. Turing in 1952. His breakthrough conceptions of chemical self-organization were able to explain how patterns emerge in nature and the symmetry breaking, which are of utmost importance, for instance, in the context of origin of life. Along with the experimental observations in the Belousov-Zhabotinsky reaction and the development of the nonequilibrium thermodynamics by Prigogine and co-workers, Turing predictions are considered the foundation of the field of Nonlinear Chemical Dynamics. This review aims to describe the basis of Turing structures with their consequent scientific achievements and to provide future directions in the development of this field. Keywords: Turing patterns; self-organization; nonlinear dynamics; pattern formation; oscillations. INTRODUÇÃOA prevalência de padrões auto-organizados em seres vivos é um resultado característico da seleção natural.1 Ao longo do tempo, o padrão que melhor se adapta ao ambiente externo é selecionado e transmitido para as gerações seguintes. Pode-se citar como um exemplo recorrente desta estruturação, a formação de moléculas de ácido desoxirribonucleico (deoxyribonucleic acid, DNA) capazes de carregar informações codificadas estritamente necessárias para a concepção de estruturas complexas em escala supramolecular. 2A autorreplicação dessas moléculas é regida por uma maquinaria reprodutiva de divisão celular que, em determinadas condições, desencadeia um processo de diferenciação e, consequentemente, um conjunto de células ou órgãos com funcionalidades específicas. Este desenvolvimento celular seletivo é conhecido por morfogênese. A primeira descrição químico-matemática desse processo foi formulada por Turing em 1952 em seu trabalho: The Chemical Basis of Morphogenesis. 3Alan Mathison Turing (23/06/1912 -7/06/1954) foi um matemá-tico britânico e criptoanalista conhecido sobretudo pela fundação da ciência da computação, criando o conceito de algoritmo e computação com a "Máquina de Turing".6 Trabalhou durante a Segunda Guerra Mundial à serviço do comando militar britânico no Government Code and Cypher School em Bletchley Park como decifrador de mensagens encriptadas por uma máquina desenvolvida pelos alemães chamada de "Enigma". Além da sua contribuição na ciência da computação, outro grande legado foi concebido dois anos antes do seu falecimento.Turing acreditava que padrões complexos encontrados em diversos aspectos na natureza poderiam ser descritos por meio da combinação de leis físicas simples. Basicamente, ele sugere que a formação desses padrões é regida pelo acoplamento entre os parâ-metros cinéticos da reação com fenômenos de transporte de massa de espécies químicas presentes no meio reacional. Essa descrição, ainda que simplificada, serviu como um passo inicial importante para o melhor entendimento da segregação espontânea de espécies químicas ao longo do espaço observada em diversos sistema...

show abstract

Chemical computing based on Turing patterns in two coupled cells with equal transport coefficients

Abstract: Two diffusively coupled reaction cells with a nonlinear reaction are used to perform chemical computing based on targeted perturbations switching between two Turing patterns defining two states of a logical device.

Cited by 12 publications

References 65 publications

Applications of Information Theory Methods for Evolutionary Optimization of Chemical Computers

Applications of Information Theory Methods for Evolutionary Optimization of Chemical Computers

Advanced Chemical Computing Using Discrete Turing Patterns in Arrays of Coupled Cells

Turing Patterns in Chemical Systems

Contact Info

Product

Resources

About