DNA Computing
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From DNA Nanotechnology to Material Systems Engineering
PROGRESS REPORT DNA Nanotechnology www.advmat.de From DNA Nanotechnology to Material Systems Engineering Yong Hu and Christof M. Niemeyer* supramolecular networks. These devel- In the past 35 years, DNA nanotechnology has grown to a highly innovative opments have given rise to numerous and vibrant field of research at the interface of chemistry, materials science, so-called “DNA tiles” that can be used as biotechnology, and nanotechnology. Herein, a short summary of the state building blocks for the assembly through of research in various subdisciplines of DNA nanotechnology, ranging from sticky-end cohesion into discrete “finite” objects or periodic “infinite” 2D and 3D pure “structural DNA nanotechnology” over protein–DNA assemblies, periodic lattices.[4] However, since the nanoparticle-based DNA materials, and DNA polymers to DNA surface production of finite DNA nanostructures technology is given. The survey shows that these subdisciplines are growing from DNA tiles remained complicated,[5] ever closer together and suggests that this integration is essential in order to the development of the “scaffolded DNA initiate the next phase of development. With the increasing implementation origami” technique by Rothemund[6] is of machine-based approaches in microfluidics, robotics, and data-driven to be seen as an important milestone. Indeed, this method enabled the break- science, DNA-material systems will emerge that could be suitable for through of DNA nanotechology for the applications in sensor technology, photonics, as interfaces between technical fabrication of finite, programmable, and systems and living organisms, or for biomimetic fabrication processes. addressable nanostructures, thereby initi- ating a second wave of innovation in the field.[7] As discussed in Section 2, this set 1. -
Algorithms for Nucleic Acid Sequence Design
Algorithms for Nucleic Acid Sequence Design Thesis by Joseph N. Zadeh In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy California Institute of Technology Pasadena, California 2010 (Defended December 8, 2009) ii © 2010 Joseph N. Zadeh All Rights Reserved iii Acknowledgements First and foremost, I thank Professor Niles Pierce for his mentorship and dedication to this work. He always goes to great lengths to make time for each member of his research group and ensures we have the best resources available. Professor Pierce has fostered a creative environment of learning, discussion, and curiosity with a particular emphasis on quality. I am grateful for the tremendously positive influence he has had on my life. I am fortunate to have had access to Professor Erik Winfree and his group. They have been very helpful in pushing the limits of our software and providing fun test cases. I am also honored to have two other distinguished researchers on my thesis committee: Stephen Mayo and Paul Rothemund. All of the work presented in this thesis is the result of collaboration with extremely talented individuals. Brian Wolfe and I codeveloped the multiobjective design algorithm (Chapter 3). Brian has also been instru- mental in finessing details of the single-complex algorithm (Chapter 2) and contributing to the parallelization of NUPACK’s core routines. I would also like to thank Conrad Steenberg, the NUPACK software engineer (Chapter 4), who has significantly improved the performance of the site and developed robust secondary structure drawing code. Another codeveloper on NUPACK, Justin Bois, has been a good friend, mentor, and reliable coding partner. -
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. -
Abstract Booklet
Abstract Booklet ONLINE EVENT 26th International Conference on DNA Computing and Molecular Programming 14–17 September 2020 IOP webinars for the physics community dna26.iopconfs.org/ Contents Committees 2 Sponsors 3 Proceedings 3 Programme 4 Poster programme 8 Keynote presentations 11 Contributed presentations 17 Poster sessions 48 1 Committees Chairs • Andrew Phillips, Microsoft Research, Cambridge, UK • Andrew Turberfield, Department of Physics, University of Oxford, UK Programme Chairs • Cody Geary, Interdisciplinary Nanoscience Centre, University of Aarhus, Denmark • Matthew Patitz, Department of Computer Science and Computer Engineering, University of Arkansas Steering Committee • Luca Cardelli, Computer Science, Oxford University, UK • Anne Condon (Chair), Computer Science, University of British Columbia, Canada • Masami Hagiya, Computer Science, University of Tokyo, Japan • Natasha Jonoska, Mathematics, University of Southern Florida, USA • Lila Kari, Computer Science, University of Waterloo, Canada • Chengde Mao, Chemistry, Purdue University, USA • Satoshi Murata, Robotics, Tohoku University, Japan • John H. Reif, Computer Science, Duke University, USA • Grzegorz Rozenberg, Computer Science, University of Leiden, The Netherlands • Rebecca Schulman, Chemical and Biomolecular Engineering, Johns Hopkins University, USA • Nadrian C. Seeman, Chemistry, New York University, USA • Friedrich Simmel, Physics, Technical University Munich, Germany • David Soloveichik, Electrical and Computer Engineering, The University of Texas at Austin, -
DNA Nanotechnology Meets Nanophotonics
DNA nanotechnology meets nanophotonics Na Liu 2nd Physics Institute, University of Stuttgart, Pfaffenwaldring 57, 70569 Stuttgart, Germany Max Planck Institute for Solid State Research, Heisenbergstrasse 1, 70569 Stuttgart, Germany Email: [email protected] Key words: DNA nanotechnology, nanophotonics, DNA origami, light matter interactions Call-out sentence: It will be very constructive, if more research funds become available to support young researchers with bold ideas and meanwhile allow for failures and contingent outcomes. The first time I heard the two terms ‘DNA nanotechnology’ and ‘nanophotonics’ mentioned together was from Paul Alivisatos, who delivered the Max Planck Lecture in Stuttgart, Germany, on a hot summer day in 2008. In his lecture, Paul showed how a plasmon ruler containing two metallic nanoparticles linked by a DNA strand could be used to monitor nanoscale distance changes and even the kinetics of single DNA hybridization events in real time, readily correlating nanoscale motion with optical feedback.1 Until this day, I still vividly remember my astonishment by the power and beauty of these two nanosciences, when rigorously combined together. In the past decades, DNA has been intensely studied and exploited in different research areas of nanoscience and nanotechnology. At first glance, DNA-based nanophotonics seems to deviate quite far from the original goal of Nadrian Seeman, the founder of DNA nanotechnology, who hoped to organize biological entities using DNA in high-resolution crystals. As a matter of fact, DNA-based nanophotonics does closely follow his central spirit. That is, apart from being a genetic material for inheritance, DNA is also an ideal material for building molecular devices. -
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 -
Analysis of Interacting Nucleic Acids in Dilute Solutions
Analysis of Interacting Nucleic Acids in Dilute Solutions Thesis by Justin S. Bois In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy California Institute of Technology Pasadena, California 2007 (Defended April 30, 2007) ii © 2007 Justin S. Bois All Rights Reserved iii Acknowledgements First and foremost, I thank Prof. Niles Pierce. He has provided me with a working environment where I am free to explore topics that spark my curiosity, all the while participating in an ambitious research program making nucleic acids do things I never imagined they could. He is a good scientific citizen, committed to ethically and passionately conducting meaningful research, providing quality instruction in the classroom, reaching out to the youth in the community, and improving the Institute as a whole. In the last several years, he has profoundly influenced my development as a scientist, leading by example with skill, enthusiasm, and integrity. I have had the good fortune of being co-advised by (and being a teaching-assistant with) Prof. Zhen- Gang Wang. He has consistently provided clear, patient advice. His depth of understanding is apparent in his comments, and also in his probing questions. He has encouraged me to think deeply about scientific problems and to distill them to their essentials. He has very generously shared his talents with me, and I am very grateful. My other two committee members have also been very helpful to me in the past couple of years. Prof. Erik Winfree and his group are close collaborators, also being creative with nucleic acids. I have had many fruitful discussions with him, finding them both challenging and enjoyable. -
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. -
Suzanne Pfeffer
July 2010 ASBMB PreSidentiAl PriMer: Suzanne Pfeffer American Society for Biochemistry and Molecular Biology AAdjuvdjuvAAntnt IImmunothermmunotherAApypy ususIIngng KKrnrn70007000 KRN7000 (α-Galactosyl Ceramide) Avanti Number 867000 Supplier: Funakoshi Co. Ltd. Hepatic metastasis is a major clinical problem in cancer treatment. We examined antitumor ac- tivity of alpha-galactosylceramide (KRN7000) on mice with spontaneous liver metastases of re- ticulum cell sarcoma M5076 tumor cells (spontaneous metastasis model). In this model, all mice that were s.c. challenged with one million tumor cells developed a solid s.c. mass by day 7 and died of hepatic metastases. In the current study, we administered 100 microg/kg of KRN7000 to the model mice on days 7, 11, and 15. This treatment suppressed the growth of established liver metastases and resulted in the prolongation of survival time. Fluorescence-activated cell sorter analysis of phenotypes of spleen cells, hepatic lymphocytes, and regional lymph node cells around the s.c. tumor revealed that CD3+NK1.1+ (NKT) cells increased in hepatic lym- phocytes of the KRN7000-treated mice. Cytotoxic activity and IFN-gamma production of hepatic lymphocytes were augmented in comparison with those of spleen cells and regional LN cells. At the same time, interleukin (IL)-12 production of hepatic lymphocytes was markedly enhanced. Neutralization of IL-12 using a blocking monoclonal antibody diminished the prolonged survival time. These results showed that the in vivo antitumor effects of KRN7000 on spontaneous liver metastases were dependent on the endogenous IL-12 production, where NKT cells in the liver are suggested to be involved. Adjuvant immunotherapy using KRN7000 could be a promising modality for the prevention of postoperative liver metastases. -
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.