DNA Computing: a Complete Overview
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DNA Computers for Work and Play
INFORMATION SCIENCE COMPUTERS DNA FOR WORK AND PL AY TIC-TAC-TOE-PLAYING COMPUTER consisting of DNA strands in solution demonstrates the potential of molecular logic gates. © 2008 SCIENTIFIC AMERICAN, INC. Logic gates made of DNA could one day operate in your bloodstream, collectively making medical decisions and taking action. For now, they play a mean game of in vitro tic-tac-toe By Joanne Macdonald, Darko Stefanovic and Milan N. Stojanovic rom a modern chemist’s perspective, the mentary school in Belgrade, Serbia, we hap- structure of DNA in our genes is rather pened to be having dinner, and, encouraged by Fmundane. The molecule has a well-known some wine, we considered several topics, includ- importance for life, but chemists often see only ing bioinformatics and various existing ways of a uniform double helix with almost no function- using DNA to perform computations. We decid- al behavior on its own. It may come as a surprise, ed to develop a new method to employ molecules then, to learn that this molecule is the basis of a to compute and make decisions on their own. truly rich and strange research area that bridges We planned to borrow an approach from synthetic chemistry, enzymology, structural electrical engineering and create a set of molec- nanotechnology and computer science. ular modules, or primitives, that would perform Using this new science, we have constructed elementary computing operations. In electrical molecular versions of logic gates that can oper- engineering the computing primitives are called ate in water solution. Our goal in building these logic gates, with intuitive names such as AND, DNA-based computing modules is to develop OR and NOT. -
Natural Computing Conclusion
Introduction Natural Computing Conclusion Natural Computing Dr Giuditta Franco Department of Computer Science, University of Verona, Italy [email protected] For the logistics of the course, please see the syllabus Dr Giuditta Franco Slides Natural Computing 2017 Introduction Natural Computing Natural Computing Conclusion Natural Computing Natural (complex) systems work as (biological) information elaboration systems, by sophisticated mechanisms of goal-oriented control, coordination, organization. Computational analysis (mat modeling) of life is important as observing birds for designing flying objects. "Informatics studies information and computation in natural and artificial systems” (School of Informatics, Univ. of Edinburgh) Computational processes observed in and inspired by nature. Ex. self-assembly, AIS, DNA computing Ex. Internet of things, logics, programming, artificial automata are not natural computing. Dr Giuditta Franco Slides Natural Computing 2017 Introduction Natural Computing Natural Computing Conclusion Bioinformatics versus Infobiotics Applying statistics, performing tools, high technology, large databases, to analyze bio-logical/medical data, solve problems, formalize/frame natural phenomena. Ex. search algorithms to recover genomic/proteomic data, to process them, catalogue and make them publically accessible, to infer models to simulate their dynamics. Identifying informational mechanisms underlying living systems, how they assembled and work, how biological information may be defined, processed, decoded. New -
Alternative Computational Models: a Comparison of Biomolecular and Quantum Computation
Alternative Computational Models: A Comparison of Biomolecular and Quantum Computation John H. Reif Department of Computer Science Duke University ∗ Abstract Molecular Computation (MC) is massively parallel computation where data is stored and processed within objects of molecular size. Biomolecular Computation (BMC) is MC using biotechnology techniques, e.g. recombinant DNA operations. In contrast, Quantum Computation (QC) is a type of computation where unitary and measurement operations are executed on linear superpositions of basis states. Both BMC and QC may be executed at the micromolecular scale by a variety of methodologies and technologies. This paper surveys various methods for doing BMC and QC and discusses the considerable theoretical and practical advances in BMC and QC made in the last few years. We compare bounds on key resource such as time, volume (number of molecules times molecular density), energy and error rates achievable, taking particular note of the scalability of these methods with the size of the problem solved. In addition to NP search problems and database search problems, we enumerate a wide variety of further potential practical applications of BMC and QC. We observe that certain problems (e.g., NP search problems), if solved with polynomial time bounds, requires exponentially large volume for BMC, so BMC does not scale well to solve very large NP search problems. However, we describe a number of applications (e.g., search within large data bases and simu- lation of parallel machines) where the volume grows polynomial. Also, we note that the observation operation of QC, which is a fundamental operation of QC used for obtaining classical output, may potentially suffer from exponentially large volume requirements. -
Solving Travelling Salesman Problem in a Simulation of Genetic Algorithms with Dna
International Journal "Information Theories & Applications" Vol.15 / 2008 357 SOLVING TRAVELLING SALESMAN PROBLEM IN A SIMULATION OF GENETIC ALGORITHMS WITH DNA Angel Goñi Moreno Abstract: In this paper it is explained how to solve a fully connected N-City travelling salesman problem (TSP) using a genetic algorithm. A crossover operator to use in the simulation of a genetic algorithm (GA) with DNA is presented. The aim of the paper is to follow the path of creating a new computational model based on DNA molecules and genetic operations. This paper solves the problem of exponentially size algorithms in DNA computing by using biological methods and techniques. After individual encoding and fitness evaluation, a protocol of the next step in a GA, crossover, is needed. This paper also shows how to make the GA faster via different populations of possible solutions. Keywords: DNA Computing, Evolutionary Computing, Genetic Algorithms. ACM Classification Keywords: I.6. Simulation and Modeling, B.7.1 Advanced Technologies, J.3 Biology and Genetics Introduction In a short period of time DNA based computations have shown lots of advantages compared with electronic computers. DNA computers can solve combinatorial problems that an electronic computer cannot like the well known class of NP complete problems. That is due to the fact that DNA computers are massively parallel [Adleman, 1994]. However, the biggest disadvantage is that until now molecular computation has been used with exact and “brute force” algorithms. It is necessary for DNA computation to expand its algorithmic techniques to incorporate aproximative and probabilistic algorithms and heuristics so the resolution of large instances of NP complete problems will be possible. -
The Many Facets of Natural Computing
The Many Facets of Natural Computing Lila Kari0 Grzegorz Rozenberg Department of Computer Science Leiden Inst. of Advanced Computer Science University of Western Ontario Leiden University, Niels Bohrweg 1 London, ON, N6A 5B7, Canada 2333 CA Leiden, The Netherlands [email protected] Department of Computer Science University of Colorado at Boulder Boulder, CO 80309, USA [email protected] “Biology and computer science - life and computation - are various natural phenomena. Thus, rather than being over- related. I am confident that at their interface great discoveries whelmed by particulars, it is our hope that the reader will await those who seek them.” (L.Adleman, [3]) see this article as simply a window onto the profound rela- tionship that exists between nature and computation. There is information processing in nature, and the natu- 1. FOREWORD ral sciences are already adapting by incorporating tools and Natural computing is the field of research that investi- concepts from computer science at a rapid pace. Conversely, gates models and computational techniques inspired by na- a closer look at nature from the point of view of information ture and, dually, attempts to understand the world around processing can and will change what we mean by computa- us in terms of information processing. It is a highly in- tion. Our invitation to you, fellow computer scientists, is to terdisciplinary field that connects the natural sciences with take part in the uncovering of this wondrous connection.1 computing science, both at the level of information tech- nology and at the level of fundamental research, [98]. As a matter of fact, natural computing areas and topics come in many flavours, including pure theoretical research, algo- 2. -
The Nanobank Database Is Available at for Free Use for Research Purposes
Forthcoming: Annals of Economics and Statistics (Annales d’Economie et Statistique), Issue 115/116, in press 2014 NBER WORKING PAPER SERIES COMMUNITYWIDE DATABASE DESIGNS FOR TRACKING INNOVATION IMPACT: COMETS, STARS AND NANOBANK Lynne G. Zucker Michael R. Darby Jason Fong Working Paper No. 17404 http://www.nber.org/papers/w17404 NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138 September 2011 Revised March 2014 The construction of Nanobank was supported under major grants from the National Science Foundation (SES- 0304727 and SES-0531146) and the University of California’s Industry-University Cooperative Research Program (PP9902, P00-04, P01-02, and P03-01). Additional support was received from the California NanoSystems Institute, Sun Microsystems, Inc., UCLA’s International Institute, and from the UCLA Anderson School’s Center for International Business Education and Research (CIBER) and the Harold Price Center for Entrepreneurial Studies. The COMETS database (also known as the Science and Technology Agents of Revolution or STARS database) is being constructed for public research use under major grants from the Ewing Marion Kauffman Foundation (2008- 0028 and 2008-0031) and the Science of Science and Innovation Policy (SciSIP) Program at the National Science Foundation (grants SES-0830983 and SES-1158907) with support from other agencies. Our colleague Jonathan Furner of the UCLA Department of Information Studies played a leading role in developing the methodology for selecting records for Nanobank. We are indebted to our scientific and policy advisors Roy Doumani, James R. Heath, Evelyn Hu, Carlo Montemagno, Roger Noll, and Fraser Stoddart, and to our research team, especially Amarita Natt, Hsing-Hau Chen, Robert Liu, Hongyan Ma, Emre Uyar, and Stephanie Hwang Der. -
Computing with DNA
International Journal of Scientific and Research Publications, Volume 3, Issue 11, November 2013 1 ISSN 2250-3153 Computing With DNA Pratiyush Guleria NIELIT, Chandigarh, Extension Centre, Shimla, Himachal Pradesh, INDIA Abstract- This paper presents a DNA Computing potential in class of problems that is difficult or impossible to solve using areas of encryption, genetic programming, language systems, and traditional computing methods. It's an example of computation at algorithms. DNA computing takes advantage of DNA or related a molecular level, potentially a size limit that may never be molecules for storing information and biotechnological reached by the semiconductor industry. It demonstrates unique operations for manipulating this information. A DNA computer aspects of DNA as a data structure. It demonstrates that has extremely dense information storage capacity, provides computing with DNA can work in a massively parallel fashion. tremendous parallelism, and exhibits extraordinary energy In 2001, scientists at the Weizmann Institute of Science in Israel efficiency. DNA computing devices could revolutionize the announced that they had manufactured a computer so small that a pharmaceutical and biomedical fields. It involves application of single drop of water would hold a trillion of the machines. The information technology to the management of biological devices used DNA and enzymes as their software and hardware information. DNA Computing is brought into focus mainly and could collectively perform a billion operations a second. because of three research directions. First, the size of Now the same team, led by Ehud Shapiro, has announced a novel semiconductor devices approaches the scale of large model of its bimolecular machine that no longer requires an macromolecules. -
DNA Computers
Eindhoven Honours Class Foundations of Informatics Algorithmic Adventures DNA computing Hendrik Jan Hoogeboom Computer Science Leiden 13 december 2010 natural computation •genetic algoritms •neural networks DNA computing bio-informatics Len Adleman Molecular Computation of Solutions to Combinatorial Problem, Science, 266: 1021-1024, (Nov. 11) 1994. ―the mad scientist at work‖ http://www.usc.edu/dept/molecular-science/fm-adleman.htm Scientific American ―In other words, one could program a Turing machine to produce Watson-Crick complementary strings, factor numbers, play chess and so on. This realization caused me to sit up in bed and remark to my wife, Lori, ‗Jeez, these things could compute.‘ I did not sleep the rest of the night, trying to figure out a way to get DNA to solve problems.‖ Leonard M. Adleman - Computing with DNA Scientific American August 1998 Physicists plunder life's tool chest If we look inside the cell, we see extraordinary machines that we couldn't make ourselves, says Len Adleman. “It's a great tool chest - and we want to see what can we build with it.” Adleman created the first computer to use DNA to solve a problem. He was struck by the parallels between DNA, with its long ribbon of information, and the theoretical computer known as the Turing Machine. Nature News Service april 2003 Physicists plunder life's tool chest Adleman tackled the famous „travelling salesman‟ problem - finding the shortest route between cities. Such problems rapidly become mind- boggling. The only way is to examine every possible option. With many cities, this number is astronomical. DNA excels at getting an astronomical amount of data into a tiny space. -
DNA Computing
DNA Computing Uladzislau Maiseichykau Michael Newell Overview ● Introduction to DNA computing ● History ● Differences between DNA and traditional computing ● Potential ● Limitations ● Constructing a DNA computing experiment ● Early DNA computing ● Modern DNA computing ● Future of DNA computing What is DNA Computing? DNA computing uses DNA, chemistry, and molecular hardware instead of traditional silicon-based circuits to run calculations and computations Interest in DNA computing stems from the possibility of processing larger sets of data in a smaller space than silicon computers, and the fast-approaching physical limits to Moore’s Law History ● Initially developed by Leonard Adleman from University of Southern California in 1994 ● Used DNA to solve the Traveling Salesman problem ● In 1997, researchers from University of Rochester used DNA to create logic gates ● Researchers from Weizmann Institute of Science unveiled a programmable computing machine that used enzymes and DNA in 2002 ● 2013, the first biological transistor, the transcriptor, was created Comparison to Standard Computing “DNA computers are unlikely to become stand-alone competitors for electronic computers.” Smallest most efficient computers, modifies cells Build items vs. raw mathematics Potential ● Ultra small devices ● Self assembly (nano) - ex: Sierpinski triangle ● Exotic and new molecular structures ● Nano-Gold + DNA = 10 smaller details on chips Limitations ● Human involvement to set up each experiment/calculation ● Response times can be as slow as minutes, hours, -
Handbook of Natural Computing
Handbook of Natural Computing Springer Reference Editors • Main Editor – Grzegorz Rozenberg (LIACS, Leiden University, The Netherlands, and Computer Science Dept., University of Colorado, Boulder, USA) • Thomas Bäck (LIACS, Leiden University, The Netherlands) • Joost N. Kok (LIACS, Leiden University, The Netherlands) Details • 4 volumes, 2104 pp., published 08/12 • Printed Book: 978-3-540-92909-3 • eReference (online): 978-3-540-92910-9 • Printed Book + eReference: 978-3-540-92911-6 Overview Natural Computing is the field of research that investigates both human-designed computing inspired by nature and computing taking place in nature, that is, it investigates models and computational tech- niques inspired by nature, and also it investigates, in terms of information processing, phenomena tak- ing place in nature. Examples of the first strand of research include neural computation inspired by the functioning of the brain; evolutionary computation inspired by Darwinian evolution of species; cellular automata in- spired by intercellular communication; swarm intelligence inspired by the behavior of groups of or- ganisms; artificial immune systems inspired by the natural immune system; artificial life systems in- spired by the properties of natural life in general; membrane computing inspired by the compart- mentalized ways in which cells process information; and amorphous computing inspired by morpho- genesis. Other examples of natural-computing paradigms are quantum computing and molecular com- puting, where the goal is to replace traditional electronic hardware by, for example, bioware in molec- ular computing. In quantum computing, one uses systems small enough to exploit quantum-mechani- cal phenomena to perform computations and to perform secure communications more efficiently than classical physics and, hence, traditional hardware allows. -
What Is DNA Computing, How Does It Work, and Why It's Such a Big Deal
3/22/2019 What is DNA Computing, How Does it Work, and Why it's Such a Big Deal INNOVATION (HTTPS://INTERESTINGENGCINREYEPRTOINCGU.RCROEMNC/INIENS O(CVRAYTPIOTONC)URRENCIES) AI (AI) ROBOTICS (ROBOTICS) 3D TECHNOLOGIES (3D-TECHNOLOGIES) WEARABLES (WEARABLES) NANOTECHNOLOGY (NANOTECHNOLOGY) ADVERTISEMENT INNOVATION (HTTPS://INTERESTINGENGINEERING.COM/INNOVATION) What is DNA Computing, How Does it Work, and Why it's Such a Big Deal Scientists are making steady progress in DNA computing, but what is DNA computing and how does it work? (https://interestingengineering.com/author/john- (https:(/h/ftatpces:b(/h/otowtpkits.ct:(e/oh/rmwt.tcwp/osswmh:(/h.al/itprsntehipknraes/trd:se loeer) u=httpusr%l=3hAt%tmp2isnF%%i=32tA&rFu%uiner2t&lFe=%urhuert2rlst=Flpt=ihinshnt%ttgetp BMya rJcohh,n 2 1Lsote 201e9r is- is- is- is- is- (https://interestingengineering.com/author/john- dna- dna- dna- dna- dna- loeer) compuctoinmgp-uctoinmgp-uctoinmgp-uctoinmgp-u how- how- how- how- how- does- does- does- does- does- it- it- it- it- it- work- work- work- work- work- and- and- and- and- and- why- why- why- why- why- k its- its- its- its- its- c a such- such- such- such- suchb - d a- a- a- a- e a- e big- big- big- big- big- F deal) deal&tdeexat=l)Wdheaatl%&2dd0eeisasc%l)r2ip https://interestingengineering.com/what-is-dna-computing-how-does-it-work-and-why-its-such-a-big-deal 1/16 3/22/2019 What is DNA Computing, How Does it Work, and Why it's Such a Big Deal INNOVATION (HTTPS://INTERESTINGENGCINREYEPRTOINCGU.RCROEMNC/INIENS O(CVRAYTPIOTONC)URRENCIES) AI (AI) ROBOTICS (ROBOTICS) 3D TECHNOLOGIES (3D-TECHNOLOGIES) WEARABLES (WEARABLES) NANOTECHNOLOGY (NANOTECHNOLOGY) k c a b d e e F Pixabay (https://pixabay.com/illustrations/microbiology-dna-people-structure-163521/) For the past decade, engineers have come up against the harsh reality of physics in the pursuit of more powerful computers: transistors, the on-off switches that power the computer processor, cannot be made any smaller than they currently are. -
Opportunities and Risks of Nanotechnologies Report in Co-Operation with the OECD International Futures Programme Contents
Small sizes that matter: Small sizes that matter: Opportunities and risks of Nanotechnologies Report in co-operation with the OECD International Futures Programme Contents 1. Executive Summary 3 1.1. Nanotechnology and the market place 3 1.2. Investments in nanotechnology 4 1.3. The environmental, health and safety discussion related to nanoparticles 4 1.4. Allianz’s position on industrial insurance cover 5 2. What is nanotechnology and what makes it different? 6 2.1. Introduction 6 2.2. Nanomaterials: basic building blocks 8 2.3. Nano tools and fabrication techniques 11 2.4. Present and future areas of application 12 3. Market prospects and opportunities 14 3.1. Sectoral example: Medicine 15 3.2. Sectoral example: Food and agriculture 17 3.3. Sectoral example: Semiconductors and computing 18 3.4. Sectoral example: Textiles 20 3.5. Sectoral example: Energy 21 3.6. Nanotechnology and the situation of developing countries 22 4. Players 24 5. Nanotechnology programs of governments 26 6. What are the risks of Nanotechnology? 27 6.1. Broad range of technologies, variety of risks 27 6.2. Positive effects on human health and the environment 28 6.3. Manufactured nanoparticles 28 6.4. Nanoparticles and human health 30 6.5. Nanoparticles and the environment 35 6.6. Explosion hazards of nanoparticles 36 6.7. Self replication of miniature machines 37 6.8. Regulatory considerations of authorities and other stakeholders 38 6.9. Position of the industry 39 6.10. Position of pressure groups 40 6.11. Position of reinsurers and insurers 40 7. Chances and risks for the Allianz Group 41 7.1.