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ABSTRACT
DNA Computers have the potential to perform calculations many times faster than the world's most powerful human-built computers. DNA computers will be capable of storing billions of times more data than your personal computer. DNA computing is currently one of the fastest growing fields in both Computer Science and Biology, and its future looks extremely promising. DNA computing is the use of DNA molecules, which encode genetic information for all living things, in computers. A functional DNA "computer" of the type most people are familiar with lies many years in the future. DNA computing is useful because it has a capacity lacked by all current electronics-based computers: its massively parallel nature. DNA computers can perform a staggering number of calculations simultaneously; specifically, on the order of 10^9 calculations per mL of DNA per second! Today we have not one but several companies making "DNA chips," where DNA strands are attached to a silicon substrate in large arrays (for example Affymetrix's genechip).






CONTENTS
• Introduction ………………………………………….1
• DNA Computation …………………………………..1
• History of DNA Computing ………………………….2
• DNA: A unique data structure ………………………..4
• DNA vs. Silicon …………………………………… ..5
• DNA Computers Solves A Complex Problem ………..5
• Test tube holds a trillion computers ………………….6
• The Future of DNA Computing ………………………7
• Advantages and Disadvantages ………………………8
• Conclusions ……………………………………………9
• Bibliography








INTRODUCTION
Computer chip manufacturers are furiously racing to make the next microprocessor that will topple speed records. Microprocessors made of silicon will eventually reach their limits of speed and miniaturization. Chipmakers need a new material to produce faster computing speeds. You won't believe where scientists have found the new material they need to build the next generation of microprocessors. DNA (deoxyribonucleic acid) molecules, the material our genes are made of, have the potential to perform calculations many times faster than the world's most powerful human-built computers. DNA might one day be integrated into a computer chip to create a so-called biochip that will push computers even faster. DNA molecules have already been harnessed to perform complex mathematical problems. DNA computers will be capable of storing billions of times more data than your personal computer.
DNA Computation
DNA computing, in the literal sense, is the use of DNA (Deoxyribose Nucleic Acid) molecules, the molecules that encode genetic information for all living things, in computers. This is accomplished in a suspended solution of DNA, where certain combinations of DNA molecules are interpreted as a particular result to a problem encoded in the original molecules present. DNA computing is currently one of the fastest growing fields in both Computer Science and Biology, and its future looks extremely promising. A highly interdisciplinary study incorporating the research results of computer scientists and biologists. In the literal sense, DNA computing is the use of DNA molecules, which encode genetic information for all living things, in computers. It is accomplished in a suspended solution of DNA, where certain combinations of DNA molecules are interpreted as a particular result to a problem encoded in the original molecules present. Dr. Leonard Aldeman is a pioneer of DNA computing for his solution to solve Hamiltonian Path Problem using DNA strands.

Inventor of DNA Computer
History of DNA Computing
In 1994, Leonard M. Adleman solved an unremarkable computational problem with a remarkable technique. It was a problem that a person could solve it in a few moments or an average desktop machine could solve in the blink of an eye. It took Adleman, however, seven days to find a solution. Why then was this work exceptional? Because he solved the problem with DNA.

DNA is a natural carrier of information
The type of problem that Adleman solved is a famous one. It's formally known as a Directed Hamiltonian Path problem, but is more popularly recognized as a variant of the so-called "Traveling salesman problem". In Adleman's version of the traveling salesman problem, a hypothetical salesman tries to find a route through a set of cities so that he visits each city only once. As the number of cities increases, the problem becomes more difficult until its solution is beyond analytical analysis altogether, at which point it requires brute force search methods. TSPs with a large number of cities quickly become computationally expensive, making them impractical to solve on even the latest super-computer. Nevertheless, his work is significant for a number of reasons.
• It illustrates the possibilities of using DNA to solve a class of problems that is difficult or impossible to solve using traditional computing methods.
• It's an example of computation at a molecular level, potentially a size limit that may never be reached by the semiconductor industry.
• It demonstrates unique aspects of DNA as a data structure
• It demonstrates that computing with DNA can work in a massively parallel fashion.
Three years after Adleman's experiment, researchers at the University of Rochester developed logic gates made of DNA. Logic gates are a vital part of how your computer carries out functions that you command it to do. These gates convert binary code moving through the computer into a series of signals that the computer use to perform operations. Currently, logic gates interpret input signals from silicon transistors, and convert those signals into an output signal that allows the computer to perform complex functions.
The Rochester team's DNA logic gates are the first step toward creating a computer that has a structure similar to that of an electronic PC. Instead of using electrical signals to perform logical operations, these DNA logic gates rely on DNA code. They detect fragments of genetic material as input, splice together these fragments and form a single output. DNA computer components -- logic gates and biochips -- will take years to develop into a practical, workable DNA computer. If such a computer is ever built, scientists say that it will be more compact, accurate and efficient than conventional computers.
DNA: A unique data structure
The data density of DNA is impressive. Just like a string of binary data is encoded with ones and zeros, a strand of DNA is encoded with four bases, represented by the letters A, T, C& G. It is also known as nucleotides, they are spaced every 0.35 nm along the DNA molecule, giving DNA a remarkable data density of nearly 18 Mbits/inch. In two dimensions, if you assume one base per square nanometer, the data density is over one million Gbits/sq inch. Compare this to the data density of a typical high performance hard drive, which is about 7 Gbits/sq inch -- a factor of over 100,000 smaller. Another important property of DNA is its double stranded nature. The bases A & T, and C & G, can bind together, forming base pairs. Therefore every DNA sequence has a natural complement. For example if sequence S is ATTACGTCG, its complement, S', is TAATGCAGC. Both S and S' will come together to form double stranded DNA. This complementarity’s makes DNA a unique data structure for computation and can be exploited in many ways. Occasionally, DNA enzymes simply make mistakes, cutting where they shouldn't, or inserting a T for a G. DNA can also be damaged by thermal energy and UV energy from the sun.
DNA vs. Silicon
DNA, with its unique data structure and ability to perform many parallel operations, allows you to look at a computational problem from a different point of view. Of course there are multi-processor computers, and modern CPUs incorporate some parallel processing, but in general, in the basic von Neumann architecture computer, instructions are handled sequentially. A von Neumann machine, which is what all modern CPUs are, basically repeats the same "fetch and execute cycle" over and over again; it fetches an instruction and the appropriate data from main memory, and it executes the instruction. It does this many, many times in a row, really, really fast. Typically, increasing performance of silicon computing means faster clock cycles (and larger data paths), where the emphasis is on the speed of the CPU and not on the size of the memory.
DNA Computers Solves A Complex Problem
A DNA-based computer has solved a logic problem that no person could complete by hand, setting a new milestone for this infant technology that could someday surpass the electronic digital computer in certain areas. USC computer science professor Dr. Leonard Adleman carried out this experiment. His experiment proved that computing with molecules was possible. But the problem solved -- to find the shortest route among seven cities -- could easily have been solved by a person with a pencil and paper.Researchers think computers made from DNA would be well suited to tackle problems that are time-consuming for conventional computers. Sequences of DNA can be crafted to represent specific patterns of information, and chemical reactions manipulate the DNA -- much as mathematical computations operate on information stored in today's computers. One such problem is depicted above: An airline serves six cities, but not all of the cities have nonstop service with each other. What is the largest group of cities that all have nonstop service with one another? The answer is four (cities 2, 3, 4,& 5).

Test tube holds a trillion computers
Researchers at the Weizmann Institute in Israel have developed a computer so small that a trillion of its kind fit into a test tube.The nanocomputer consists of DNA and DNA-processing enzymes, both dissolved in a liquid.The inventors believe it could ultimately lead to a device capable of processing DNA inside the human body, finding abnormalities and creating healing drugs. In the medium term, it could be turned into a tool capable of speeding up the currently labour intensive job of DNA sequencing. Professor Ehud Shapiro, head of the Weizmann team, says the DNA computer is an automaton, completing its work without human intervention at each stage of processing. Today it is limited to processing DNA, which is synthetically designed. In the future it could process any DNA molecules. The machine's input, output and software program are all DNA molecules.



Previous efforts
DNA computing took a leap forwards in 1994 when Leonard Adleman of the University of Southern California used DNA. It stores a massive amount of data in a small space. Its effective density is roughly 100,000 times greater than modern hard disks. And while a desktop PC concentrates on doing one task at a time very quickly, billions of DNA molecules in a jar will attack the same problem billions of times over. Their goal was not to harness the power of biological computing to solve weighty mathematical problems, but to build a nanoscale computer, which takes naturally occurring information-bearing biological molecules such as DNA as an input. Their success in creating a nanomachine that works on synthetically produced short DNA strands is a huge step towards this goal.
The Future of DNA Computing
Currently, molecular computing is a field with a great deal of potential, but few results of practical value. In the wake of Adleman's solution of the Hamiltonian path problem, there came a host of other articles on computation with DNA; however, most of them were purely theoretical. Currently, a functional DNA "computer" of the type most people are familiar with lies many years in the future. But work continues: in his article Speeding Up Computation via Molecular Biology Lipton shows how DNA can be used to construct a Turing machine, a universal computer capable of performing any calculation. While it currently exists only in theory, it's possible that in the years to come computers based on the work of Adleman, Lipton, and others will come to replace traditional silicon-based machines.

ADVANTAGES AND DISADVANTAGES
DNA computing is useful because it has a capacity lacked by all current electronics-based computers: its massively parallel nature. DNA computers can perform a staggering number of calculations simultaneously; specifically, on the order of 10^9 calculations per mL of DNA per second! This capability of multiple cotemporal calculations immediately lends itself to several classes of problems which a modern electronic computer could never even approach solving.
DNA computers do have their disadvantages. To make these computers more realistically viable, the DNA splicing and selection equipment needs to be refined for this purpose and better methods for fishing developed. There is also no guarantee that the solution produced will necessarily be the absolute best solution, though it will certainly be a very good one, arrived at in a much shorter time than with a conventional computer. DNA computers could not (at this point) replace traditional computers. Some think that in the future, computers will be a combination of the current models and DNA, using the most attractive features of both to create a vastly improved total product. And of course we are talking about DNA here, the genetic code of life itself. Considering all the attention that DNA has garnered, it isn’t too hard to imagine that one day we might have the tools and talent to produce a small-integrated desktop machine that uses DNA, or a DNA-like biopolymer, as a computing substrate along with set of designer enzymes.



CONCLUSION
This first demonstration of DNA computing used a rather unsophisticated algorithm, but as the formalism of DNA computing becomes refined, new algorithms perhaps will one day allow DNA to overtake conventional computation and set a new record. On the side of the "hardware", improvements in biotechnology are happening at a rate similar to the advances made in the semiconductor industry. Just look at the number of advances in DNA-related technology that happened in the last five years. Today we have not one but several companies making "DNA chips," where DNA strands are attached to a silicon substrate in large arrays (for example Affymetrix's genechip). Production technology of MEMS is advancing rapidly, allowing for novel integrated small-scale DNA processing devices. The Human Genome Project is producing rapid innovations in sequencing technology. The future of DNA manipulation is speed, automation, and miniaturization.
And of course we are talking about DNA here, the genetic code of life itself. It certainly has been the molecule of this century and most likely the next one. Considering all the attention that DNA has garnered, it isn’t too hard to imagine that one day we might have the tools and talent to produce a small-integrated desktop machine that uses DNA, or a DNA-like biopolymer, as a computing substrate along with set of designer enzymes. Perhaps it won’t be used to play Quake IV or surf the web -- things that traditional computers are good.