Sticker systems

DNA computing, or more generally, molecular computing, is a recent development on computations using biological molecules, instead of the traditional silicon-chips. Some computational models which are based on different operations of DNA molecules have been developed by using the concept of formal language theory. The operations of DNA molecules inspire various types of formal language tools which include sticker systems, grammars and automata. Recently, the grammar counterparts of Watson-Crick automata known as Watson-Crick grammars which consist of regular, linear and context-free grammars, are defined as grammar models that generate double-stranded strings using the important feature of Watson-Crick complementarity rule. In this research, a new variant of static Watson-Crick linear grammar is introduced as an extension of static Watson-Crick regular grammar. A static Watson-Crick linear grammar is a grammar counterpart of sticker system that generates the double-stranded strings and uses rule as in linear grammar. The main result of the paper is to determine some computational properties of static Watson-Crick linear grammars. Next, the hierarchy between static Watson-Crick languages, Watson-Crick languages, Chomsky languages and families of languages generated by sticker systems are presented.

Molecular computing has gained many interests among researchers since Head introduced the first theoretical model for DNA based computation using the splicing operation in 1987. Another model for DNA computing was proposed by using the sticker operation which Adlemanused in his successful experiment for the computation of Hamiltonian paths in a graph: a double stranded DNA sequence is composed by prolonging to the left and to the right a sequence of (single or double) symbols by using given single stranded strings or even more complex dominoes with sticky ends, gluing these ends together with the sticky ends of the current sequence according to a complementarity relation. According to this sticker operation, a language generative mechanism, called a sticker system, can be defined: a set of (incomplete) double-stranded sequences (axioms) and a set of pairs of single or double-stranded complementary sequences are given. The initial sequences are prolonged to the left and to the right by using sequences from the latter set, respectively. The iterations of these prolongations produce “computations” of possibly arbitrary length. These processes stop when a complete double stranded sequence is obtained. Sticker systems will generate only regular languages without restrictions. Additional restrictions can be imposed on the matching pairs of strands to obtain more powerful languages. Several types of sticker systems are shown to have the same power as regular grammars; one type is found to represent all linear languages whereas another one is proved to be able to represent any recursively enumerable language. The main aim of this research is to introduce and study sticker systems over monoids in which with each sticker operation, an element of a monoid is associated and a complete double stranded sequence is considered to be valid if the computation of the associated elements of the monoid produces the neutral element. Moreover, the sticker system over monoids is defined in this study.

DNA computing is an area of natural computing based on the idea that molecular biology processes can be used to perform arithmetic and logic operations on information encoded as DNA strands. The first part of this review outlines basic molecular biology notions necessary for understanding DNA computing, recounts the first experimental demonstration of DNA computing (Adleman’s 7-vertex Hamiltonian Path Problem), and recounts the milestone wet laboratory experiment that first demonstrated the potential of DNA computing to outperform the computational ability of an unaided human (20 variable instance of 3-SAT).The second part of the review describes how the properties of DNA-based information, and in particular the Watson–Crick complementarity of DNA single strands, have influenced areas of theoretical computer science such as formal language theory, coding theory, automata theory and combinatorics on words. More precisely, we describe the problem of DNA encodings design, present an analysis of intramolecular bonds, define and characterize languages that avoid certain undesirable intermolecular bonds, and investigate languages whose words avoid even imperfect bindings between their constituent strands. We also present another, vectorial, representation of DNA strands, and two computational models based on this representation: sticker systems and Watson–Crick automata. Lastly, we describe the influence that properties of DNA-based information have had on research in combinatorics on words, by enumerating several natural generalizations of classical concepts of combinatorics of words: pseudopalindromes, pseudoperiodicity, Watson–Crick conjugate and commutative words, involutively bordered words, pseudoknot bordered words. In addition, we outline natural extensions in this context of two of the most fundamental results in combinatorics of words, namely Fine and Wilf's theorem and the Lyndon–Schutzenberger result.

Design of data structure is valuable to the concrete realization of DNA computer.Therefore,a method of designing a binary tree based on sequential storage model in DNA computer was proposed,which utilized the biological characteristics of DNA molecules and restriction endonucleases to complete sequential storage structure and basic operations of the binary tree.All the biological technology mentioned here could be practically implemented in the laboratory.To prove the feasibility of this method,an actual binary tree with detailed nucleotide encodings and an instance of algorithm were given.The process of an algorithm implemented on this binary tree was demonstrated.

This paper addresses two main aspects of DNA computing research: DNA computing in vitro and in vivo. We first present a model of DNA computation developed in [5]: the circular insertion/deletion system. We review the result obtained in [5] stating that this system has the computational power of a Turing machine, and present the outcome of a molecular biologylab oratoryex periment from [5] that implements a small instance of such a system. This shows that rewriting systems of the circular insertion/deletion type are viable alternatives in DNA computation in vitro. In the second half of the paper we address DNA computing in vivo by presenting a model proposed in [17] and developed in [18] for the homologous recombinations that take place during gene rearrangement in ciliates. Such a model has universal computational power which indicates that, in principle, some unicellular organisms may have the capacity to perform any computation carried out by an electronic computer.KeywordsTuring MachineFormal LanguageCircular StringDeletion RuleIntramolecular RecombinationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Molecular computers (also called DNA computers), as an alternative to traditional electronic computers, are smaller in size but more energy efficient, and have massive parallel processing capacity. However, DNA computers may not outperform electronic computers owing to their higher error rates and some limitations of the biological laboratory. The stickers model, as a typical DNA-based computer, is computationally complete and universal, and can be viewed as a bit-vertically operating machine. This makes it attractive for silicon implementation. Inspired by the information processing method on the stickers computer, we propose a novel parallel computing model called DEM (DNA Electronic Computing Model) on System-on-a-Programmable-Chip (SOPC) architecture. Except for the significant difference in the computing medium—transistor chips rather than bio-molecules—the DEM works similarly to DNA computers in immense parallel information processing. Additionally, a plasma display panel (PDP) is used to show the change of solutions, and helps us directly see the distribution of assignments. The feasibility of the DEM is tested by applying it to compute a maximum clique problem (MCP) with eight vertices. Owing to the limited computing sources on SOPC architecture, the DEM could solve moderate-size problems in polynomial time.

We introduce a new model of molecular computation that we call the sticker model. Like many previous proposals it makes use of DNA strands as the physical substrate in which information is represented and of separation by hybridization as a central mechanism. However, unlike previous models, the stickers model has a random access memory that requires no strand extension and uses no enzymes; also (at least in theory), its materials are reusable. The paper describes computation under the stickers model and discusses possible means for physically implementing each operation. Finally, we go on to propose a specific machine architecture for implementing the stickers model as a microprocessor-controlled parallel robotic workstation. In the course of this development a number of previous general concerns about molecular computation (Smith, 1996; Hartmanis, 1995; Linial et al., 1995) are addressed. First, it is clear that general-purpose algorithms can be implemented by DNA-based computers, potentially solving a wide class of search problems. Second, we find that there are challenging problems, for which only modest volumes of DNA should suffice. Third, we demonstrate that the formation and breaking of covalent bonds is not intrinsic to DNA-based computation. Fourth, we show that a single essential biotechnology, sequence-specific separation, suffices for constructing a general-purpose molecular computer. Concerns about errors in this separation operation and means to reduce them are addressed elsewhere (Karp et al., 1995; Roweis and Winfree, 1999). Despite these encouraging theoretical advances, we emphasize that substantial engineering challenges remain at almost all stages and that the ultimate success or failure of DNA computing will certainly depend on whether these challenges can be met in laboratory investigations.

DNA computer is a new type of computer which computing by biological molecular techniques. If DNA computer want to realize its practicability, it must be the same as a traditional computer. In order to settle the issues of representation and organizational in DNA computer, we need a reasonable data structures to effectively represent and organize the information of DNA computer. The thesis designs a stack structure model based on DNA computing, which can express limited stack constraints through hairpin structure. At the same time, it can complete the operations of entering stack and leaving stack using two different restrictive enzymes.

DNA computing aims at using nucleic acids for computing. Since micromolar DNA solutions can act as billions of parallel nanoprocessors, DNA computers can in theory solve optimization problems that require vast search spaces. However, the actual parallelism currently being achieved is at least a hundred million-fold lower than the number of DNA molecules used. This is due to the quantity of DNA molecules of one species that is required to produce a detectable output to the computations. In order to miniaturize the computation and considerably reduce the amount of DNA needed, we proposed that fluorescence labeling techniques can be applied to DNA computing. In the paper, we solved the simple 0-1 programming problem with fluorescence labeling techniques based on surface chemistry. It is attempt to apply DNA computing to programming problem.

Nature has remedies for almost all problems. Though biological systems exhibits organised, complex and intelligent behaviour, they comprise of simple elements and governed by simple rules. Hence, mimicking such systems has been the attraction of researchers in the fields of computer science, neuroscience and biology for a long time. Generating complex behaviour from small agents working locally following simple rules is a highly cost-effective solution of the real life problem. Bio-inspired computing can be achieved through different models such as stochastic, ad hoc or discrete models; new paradigm inspired from nature like evolutionary approach and immune systems; and new platform, novel architecture and specially designed material such as artificial fuel cell. The consortium of bio-inspired computing are artificial neural networks, evolutionary algorithms, swarm intelligence, artificial immune systems, fractal geometry, artificial life, DNA computing and quantum computing, etc. This article discusses consortium of bio-inspired computing along with applications and research scope. In spite of having advantages offered by partial simulation of natural intelligence, there are some limitations of the bio-inspired computing that need to be addressed. These challenges include creation of new model, techniques and platforms for bio-inspired computing. This article concludes with the challenges to be explored in the field.

Vve introduce a new model of molecular computation that we call the sticker model.Like many previous proposals it makes use of DNA strands as the physical substrate in which information is represented and of separation by hybridization as a central mechanism.However , unlike previous models, the stickers model has a random access memory that requires no strand extension, uses no enzymes, and (at least in theory) its materials are reusable.The paper describes computation under the stickers model and discusses possible means for physically implementing each operation.We go on to propose a specific machine architecture for implementing the stickers model as a microprocessor-controlled parallel robotic workstation.Finally, we discuss several methods for achieving acceptable overall error rates for a computation using basic operations that are error prone.In t he course of this development a number of previous general concerns about molecular computation [36, 2 0 , 24 ) are addressed.First, it is clear that general-purpose algorithms can be implemented by DNA-based computers, potentially solving a " .. •ide class of search problems.Second, we find that there are challenging problems, for which only modest volumes of DNA should suffice.Third, we demonstrate that the formation and breaking of covalent bonds is not intrinsic to DNA-based computation.This means that costly and short-lived materials such as enzymes are not necessary, nor are energetically costly processes such as PCR.Fourth , \ .... e show that a single essential biotechnology, sequence-specific separation , suffices for constructing a general-purpose molecular computer.Fifth, we illustrate that separation errors can theoretically be reduced to tolerable levels by invoking a trade-off between time, space, and error rates at the level of algorithm design; we also outline several specific ways in which this can be done and present numerical calculations of their per formance.Despite these encouraging theoretical advances , we emphasize that sub-stantial engineering challenges remain at almost all stages and that the ultimate success or failure of DNA computing will certainly depend on whether t.hese challenges can be met in laboratory investigations.

Tile assembly model is a formal model of DNA computing, which uses DNA, biochemistry and molecular biology instead of the traditional silicon-based computer technologies. DNA-based cryptography is an interdisciplinary area combining classical cryptography and molecular computing. This paper proposes how the tile assembly process could be used for computing inversion over finite field GF(2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> ), a basic mathematic operation often used in cryptography. This computing system is designed based on two other parallel molecular computing systems proposed in our previous works. Time complexity of this system is Θ(n <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) and the space complexity is Θ(n <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> ).

Supercritical fluids are fluids at temperature and pressure above their respective critical values. Such fluids are increasingly being used in power generation, refrigeration and chemical process industry. The objectives of the current research were to develop a fundamental understanding of the transport phenomena in near-critical supercritical fluids via high-resolution numerical simulations and careful experiments for improved design of industrial processes and applications that employ supercritical fluids. A set of synergistic experimental and numerical studies were proposed in this research. Four main focus areas under the broad spectrum of supercritical fluid transport were chosen - (a) characterization of thermoacoustic transport, (b) interaction of thermoacoustic transport with natural convection, (c) characterization of acoustically augmented transport and (d) enhancement of mass transport using acoustic waves. A numerical model to simulate thermoacoustic convection in near-critical fluids was developed. In the computational model, the conservation equations were solved along with a real-fluid equation of state for supercritical fluid and variable thermo-physical properties. Thermoacoustic waves in near-critical carbon dioxide were also investigated experimentally on acoustic time scales using a fast response measurement system. The predicted results from the calculation and the measurements provide interesting details regarding the thermal transport mechanisms at near-critical states. The numerical model was applied to investigate the interaction of buoyancy driven flows with thermoacoustic convection in near-critical supercritical fluids. This model can be extensively used for studying the steady-state thermal transport and stability behavior of near-critical fluids. Mechanically driven acoustic waves in supercritical fluid generated by a vibrating wall in a cylindrical resonator were studied both numerically and experimentally. The simulations revealed interesting steady-periodic flow patterns in the resonator filled with near-critical fluid due to the fluctuations caused by the vibrating wall. High-fidelity computational fluid dynamics models of mass transport processes in supercritical fluid extraction systems were also developed. A novel application of acoustically driven transport in supercritical fluid was demonstrated numerically for the supercritical fluid extraction process. The numerical predictions indicated major improvements in the extraction yield due to the application of acoustic waves and can be utilized in the design and optimization of supercritical fluid extraction systems.

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