A computer scientist's guide to molecular biology

2012

Molecular computing is computation done at the molecular scale. DNA computing is a class of molecular computing that does computation by the use of reactions involving DNA molecules. DNA computing has been far the most successful (in scale and complexity of the computations and molecular assemblies done) of all known approaches to molecular computing, perhaps due in part to the very well established biotechnology and biochemistry on which its experimental demonstration relies, as well as the frequent teaming of scientists in the field with multiple essential disciplines including chemistry, biochemistry, physics, material science, and computer science. This chapter surveys the field of DNA computing. It begins with a discussion of underlying principles, including motivation for molecular and DNA computations, brief overviews of DNA structures, chemical reaction systems, DNA reactions, and classes of protocols and computations. Then, the chapter discusses potential applications of DN...

Studies in Computational Intelligence, 2008

2002

DNA computing, or, more generally, molecular computing, is an exciting fast developing interdisciplinary area. Research in this area concerns theory, experiments, and applications of DNA computing. In this paper, we demonstrate the theoretical developments by discussing a number of selected topics. We also give an introduction to the basic structure of DNA and the basic DNA processing tools.

IEEE Transactions on Nanobioscience, 2006

DNA computation is to use DNA molecules for information storing and processing. The task is accomplished by encoding and interpreting DNA molecules in suspended solutions before and after the complementary binding reactions. DNA computation is attractive, due to its fast parallel information processing, remarkable energy efficiency, and high storing capacity. Challenges currently faced by DNA computation are (1) lack of theoretical computational models for applications, and (2) high error rate for implementation. This paper attempts to address these problems from mathematical modeling and genetic coding aspects. The first part of this paper presents a mathematical formulation of DNA computation. The model may serve as a theoretical framework for DNA computation. In the second part, a genetic code based DNA computation approach is presented to reduce error rate for implementation, which has been a major concern for DNA computation. The method provides a promising alternative to reduce error rate for DNA computation.

1997

DNA computation is a novel and exciting recent development at the interface of computer science and molecular biology. We describe the current activity in this field following the seminal work of Adleman, who recently showed how techniques of molecular biology may be applied to the solution of a computationally intractable problem.

In recent times, computer chip manufacturers are frantically racing to make the next microprocessor that will overthrow speed records. So Microprocessors made of silicon will eventually reach their limits of speed and miniaturization and their manufacturers will need a new material to produce faster computing speeds. But fortunately scientists have found the new material they need to build the next generation of microprocessors. Millions of natural supercomputers exist inside living organisms, including our body. DNA (deoxyribonucleic acid) molecules, the material our genes are made of, have the potential to perform calculations many times faster than the most powerful human-built computers. DNA might in the nearest future be integrated into a computer chip to create a so-called BIOCHIP that makes computers even faster. DNA molecules have already been harnessed to perform complex mathematical problems by researchers.While still in its early life,DNAcomputers will be capable of storing billions of times more data than today personal computer. In this article, a survey of recent research on DNA computing is discussed and the possibility that it might take the place of silicon-based computers in the next decade.

From Logic Systems to Smart Sensors and Actuators, 2012

200 1 1 Blomotecutor Computing Systems 11.2 DNA as a Tool for Molecular Programming DNA systems are relatively easy to design, fairly predictable in their geometric structures, and chemically stable, and have been experimentally implemented in a growing number of laboratories around the world. Abstractions for programming DNA systems and software tools that aid in the design, verification, and simulation of such systems have further expanded the horizons of what are feasible using DNA. Most DNA systems are autonomous: they can execute steps with no external mediation after starting, they are programmable, and the tasks executed can be modified without entirely redesigning the system. I n contrast, lipids and carbohydrates are not programmable, the function and structure of proteins are hard to design, and RNA is unstable. 11.2.1 DNA Structure Single-stranded DNA (ssDNA) is a polymer made f rom repeating units called nucleotides. The nucleotide repeats contain both the segment of the backbone of the molecule, which holds the chain together, and a base. ssDNA has asymmetries along its backbone which gives it a directionality. The asymmetric ends of ssDNA are called the 5' and 3' ends. The four bases found in DNA are adenine (abbreviated A), cytosine (C), guanine (G), and thymine (T) (Figure 11.1). These bases f orm the alphabet of DNA; the specific sequence of an ssDNA comprises its information content. I n living organisms, DNA does not usually exist as a single molecule, but instead as double-stranded DNA (dsDNA): a pair of oppositely directed ssDNA held together via complementary base binding, with A hydrogen-bonded preferentially to T, and C hydrogen-bonded preferentially to G. These two long strands entwine like vines, forming a double helix. As hydrogen bonds are not covalent, they can be broken and rejoined relatively easily, for example, by heating. The two types of base pairs form different numbers of hydrogen bonds, AT f orming two hydrogen bonds and GC forming three hydrogen bonds. The association strength of hybridization depends on the sequence of complementary bases, the stability increasing with the length of the DNA sequence, and the GC content. This association strength can be approximated by software packages. 11.2.2 Review of DNA Reactions We review a few key reactions that allow DNA to execute molecular programs. Toehold-mediated strand displacement is the displacement of a single strand of DNA from a double helix by an incoming strand with a longer complementary region to the template strand. The incoming strand has a toehold, an empty single-stranded region on the template strand complementary to a subsequence of the incoming strand, to which it binds initially. It eventually displaces the outgoing) Efficient is generally taken to mean that the algorithm's running time is some polynomial function of the size of the problem.

International Journal of Science and Research (IJSR)

DNA computing is a nascent technology that seeks to capitalize on the enormous informational capacity of DNA, biological molecules that can store huge amounts of information and are able to perform operations similar to computers through the deployment of enzymes, biological catalysts that act like software to execute desired operations i.e. Computers made of genes' building blocks. Because of their speed, miniaturization and Data Storage potential DNA computers are being considered as a replacement for silicon-based computers. Current DNA computer research has already proven that DNA computers are capable of solving complex mathematical equations and storing enormous amounts of data.

IEEE Signal Processing Magazine, 2004

2003

Deoxyribonucleic Acid or DNA computing has emerged as an interdisciplinary field that draws together chemistry, molecular biology, computer science and mathematics. Thus, in this paper, the possibility of DNA-based computing to solve an absolute 1-center problem by molecular manipulations is presented. This is truly the first attempt to solve such a problem by DNA-based computing approach. Since, part of the procedures involve with shortest path computation, research works on DNA computing for shortest path Traveling Salesman Problem, in short, TSP are reviewed. These approaches are studied and only the appropriate one is adapted in designing the computation procedures. This DNA-based computation is designed in such a way that every path is encoded by oligonucleotides and the path's length is directly proportional to the length of oligonucleotides. Using these properties, gel electrophoresis is performed in order to separate the respective DNA molecules according to their length. One expectation arise from this paper is that it is possible to verify the instance absolute 1-center problem using DNA computing by laboratory experiments.