Abstract
Silicon microprocessors have been the heart of computing world for more than forty years. Computer chip manufacturers are furiously racing to make the next microprocessor that will topple speed records. Sooner or later the physical speed and miniaturization limit of silicon microprocessors is bound to hit a wall.
Chipmakers need a new material to produce faster computing speed with fewer complexities. Itâ„¢s unbelievable where scientists have found this new material. DNA, the material our genes are made of, is being used to build the next generation of microprocessors. A nascent technology that uses DNA molecules to build computers that are faster than the worldâ„¢s most powerful human-built computers is called DNA computing. Now we are taking those tools in large numbers molecules and using them as biological computer processors.
DNA computing has a great deal of advantage over conventional silicon-based computing. DNA computers can store billions of times more data than your personal computer. DNA computers have the ability to work in a massively parallel fashion, performing many calculations simultaneously.
DNA computing has made a remarkable progress in almost every field. It has found application in fields like biomedical, pharmaceutical, information security, cracking secret codes, etc. Scientists and researchers believe that in the foreseeable future DNA computing could scale up to great heights!


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[attachment=5380]

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Introduction To DNA Computer

• Store Billions of time more information.
• High computing speed.
• Information is encoded within ‘Deoxiribo Nucleic Acid’.
• First Demonstrated By Ad leman in 1994.


Some information about DNA

• Definition of DNA
• About nucleic acid
• Genes and chromosomes

Structure of DNA

• Strands of DNA are long polymers of millions of linked nucliotides.
• Nitrogen bases .
• 5’ to 3’ direction.
• Double Helix form.
• Purin and pirimidin bases.

Operations on DNA

• Merge
• Annealing
• Melt
• Separation by length - Electophoresis.
• Separation by sequences
• Copying / Amplification
• Append
• Detect

Conclusion

• I would like to conclude by sharing a future vision in which a single drop of water holds a veritable army of live robots for protection against various
diseases may be even cancer.
• It is still science fiction but implanting computer programs in to living creatures may not be far away.

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Introduction

DNA Computer can store billions of times more information then your PC hard drive and solve complex problems in a less time.We know that computer chip manufacturers are racing to make the next microprocessor that will more faster. Microprocessors made of silicon will eventually reach their limits of speed and miniaturization. Chips makers need a new material to produce faster computing speeds.
To understand DNA computing lets first examine how the conventional computer process information. A conventional computer performs mathematical operations by using electrical impulses to manipulate zeroes and ones on silicon chips. A DNA computer is based on the fact the information is “encoded” within deoxyribonucleic acid (DNA) as as patterns of molecules known as nucleotides. By manipulating the how the nucleotides combine with each other the DNA computer can be made to process data. The branch of computers dealing with DNA computers is called

DNA Computing.

The concept of DNA computing was born in 1993, when Professor Leonard Adleman, a mathematician specializing in computer science and cryptography accidentally stumbled upon the similarities between conventional computers and DNA while reading a book by James Watson. A little more than a year after this, In 1994, Leonard M. Adleman, a professor at the University of Southern California, created a storm of excitement in the computing world when he announced that he had solved a famous computation problem. This computer solved the traveling salesman problem also known as the “Hamiltonian path" problem,which is explained later. DNA was shown to have massively parallel processing capabilities that might allow a DNA based computer to solve hard computational problems in a reasonable amount of time.
There was nothing remarkable about the problem itself, which dealt with finding the shortest route through a series of points. Nor was there anything special about how long it took Adleman to solve it — seven days — substantially greater than the few minutes it would take an average person to find a solution. What was exciting about Adleman’s achievement was that he had solved the problem using nothing but deoxyribonucleic acid (DNA) and molecular chemistry.

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seminars report on DNA Computers

[attachment=11084]
ABSTRACT
“Everything looks good when it is mounted on a chip.”
To challenge the limits of speed and miniaturization scientists of silicon chip the biochip has been invented and made up of DNA (Deoxyribonucleic acid). The function of 0’s and 1’s are done by the specified combinations of the four nucleotides. Their speed is billion times faster. As its processing is parallel and not serial it can compute problem with large possibilities much faster. With application in various fields of genetics basically DNA recognition as well as chemistry development of medicines and detecting diseases it has more utilities.
Biological and mathematical operations have some similarities, despite their respective complexities:
1. The very complex structure of a living being is the result of applying simple operations to initial information encoded in a DNA sequence;
2. The result f(w) of applying a computable function to an argument w can be obtained by applying a combination of basic simple functions to w.
For the same reasons that DNA was presumably selected for living organisms as a genetic material, its stability and predictability in reactions, DNA strings can also be used to encode information for mathematical systems.
1. INTRODUCTION TO DNA COMPUTER
Computer chip manufactures are furiously racing to make the next microprocessor that will topple speed records. Sooner or later, though, this competition is bound to hit a wall. Microprocessor made of silicon will eventually reach their limits of speed and miniaturization. Chip makers 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. Millions of natural supercomputers exist inside living organisms, including your living body.
DNA (deoxyribonucleic acid) molecules, the material our genes are made of, have the potential to perform calculations many faster than the world’s most powerful human-built computers.
What is a DNA Computer?
Research in the development of DNA computers is really only at its beginning stages, so a specific answer isn't yet available. But the general sense of such a computational device is to use the DNA molecule as a model for its construction. Although the feasibility of molecular computers remains in doubt, the field has opened new horizons and important new research problems, both for computer scientists and biologists. The computer scientist and mathematician are looking for new models of computation to replace with acting in a test tube.
The massive parallelism of DNA strands may help to deal with computational problems that are beyond the reach of ordinary digital computers not because the DNA strands are smarter, but because they can make many tries at once. It's the parallel nature of the beast. For the biologist, the unexpected results in DNA computing indicate that models of DNA computers could be significant for the study of important biological problems such as evolution. Also, the techniques of DNA manipulation developed for computational purposes could also find applications in genetic engineering. DNA computer can’t be still found at your local electronics store yet. The technology is still in their development, and didn’t exist as concept before a decade. In 1994, LEONARD ADELMAN introduced the idea of using DNA to solve complex mathematical problems.
Adelman, computer scientist at the university of Southern California, came to the conclusion that DNA had computational potential after reading the book “MOLECULAR BIOLOGY OF THE GENE” written by JAMES WASTON, who co-discovered the structure of DNA in 1953.In fact, DNA is more similar to computer. DNA is very similar to a computer hard drive in how it stores permanent information about your genes.
2. HAMILTON PATH PROBLEM
Adelman is often called the inventor of the DNA computers. His article in a 1994 issue of Journal Science outlined how to use DNA to solve a well-known mathematical problem, called the “Directed Hamilton Path problem”, also known as the “Traveling Salesman Problem”. The goal of the problem is to find the shortest route between a numbers of cities, going through each city only once. As you add more cities the problem becomes more difficult. Figure 2.1 shows a diagram of the Hamilton path problem. The objective is to find a path from start to end going through all the points only once. This problem is difficult for the conventional (serial logic) computers because they try must try each path one at a time. It is like having a whole bunch of keys and trying to see which fits into the lock. Conventional computers are very good at math, but poor at “key into lock” problems. DNA based computers can try all the keys at the same time (massively parallel) and thus are very good at key into lock problems, but much slower at simple mathematical problems like multiplication. The Hamilton path problem was chosen because every key-into-lock problem can be solved as a Hamilton Path Problem.
The following algorithm solves the Hamilton Path Problem, regardless of the type computers used.
1. Generate random paths through the graph.
2. Keep only those paths that begin with the start city (A) and conclude with the end city (G).
3. Because the graph has 7 cities, keep only those paths with 7 cities.
4. Keep only those paths that enter all cities at least once.
5. Any remaining paths are solutions.
The key to solving the problem was using DNA to perform the five steps in solving the above algorithm.
These interconnecting blocks can be used to model DNA:
DNA likes to form long double helices:
The two helices are joined by “bases”, which will be represented by coloured blocks. Each base binds only to one other specific base. In our example, we will say that each coloured block will bind only with the block of same colour. For example, if we only had red coloured blocks, they would form a long chain like this:
Any other colour will not bind with red:
3.PROGRAMMING OF THE PROBLEM USING DNA
STEP 1: Create a unique DNA sequence for each city A through G. For each path, for example, from A to B, creates a linking pieces of DNA that matches the last half of A and first half of B:
Here the red block represents the city a, while the orange block represents the city B. The half-red half-orange block connecting the two other blocks represents the path from A to B.
In a test tube, all different pieces of DNA will randomly page link with each other, forming paths through the graph.
STEP 2: Because it is difficult to "remove" DNA from solution, the target DNA, the DNA which started from A and ended at G was copied over and over again until the test tube contained a lot of it relative to other random sequences. This is essentially the same as removing all the other pieces. Imagine a sock drawer which initially contains one or two coloured socks. If you put in a hundred black socks, the chances are that all you will get if you reach in is black socks.
STEP 3: Going by weight, the DNA sequences which were 7 "cities" long were separated from the rest. A "sieve" was used which would allow smaller pieces of DNA to pass quickly, while larger segments are slowed down. the procedure used actually allows you to isolate the pieces which are precisely cities long from any shorter or longer paths.
STEP 4: To ensure that the remaining sequences went through each of cities, “sticky” pieces of DNA attached to magnets were used to separate the DNA. The magnets were used to ensure that the target DNA remained in the test tube, while the unwanted DNA was washed away. First, the magnets kept all the DNA which went through city A in the test tube, then B, then C, and D, and so on. In the end, the only DNA which remained in the tube was that which went through all seven cities.
STEP 5: all that was left to sequences the DNA, revealing the path from A to B to C to D to E to F to G.
4. WORKING OF DNA
DNA is the major information storage molecule in living cells, and billions of years of evolution have tested and refined both this wonderful informational molecule and highly specific enzymes that can either duplicate the information in DNA molecules or transmit this information to other DNA molecules. Instead of using electrical impulses to represent bits of information, the DNA computer uses the chemical properties of these molecules by examining the patterns of combination or growth of the molecules or strings. DNA can do this through the manufacture of enzymes, which are biological catalysts that could be called the 'software' used to execute the desired calculation.
DNA computers use deoxyribonucleic acids--A (adenine), C (cytosine), G (guanine) and T (thymine)--as the memory units, and recombinant DNA techniques already in existence carry out the fundamental operations. In a DNA computer, computation takes place in test tubes or on a glass slide coated in 24K gold. The input and output are both strands of DNA, whose genetic sequences encode certain information. A program on a DNA computer is executed as a series of biochemical operations, which have the effect of synthesizing, extracting, modifying and cloning the DNA strands.
The only fundamental difference between conventional computers and DNA computers is the capacity of memory units: electronic computers have two positions (on or off), whereas DNA has four (C, G, A or T). The study of bacteria has shown that restriction enzymes can be employed to cut DNA at a specific word(W). Many restriction enzymes cut the two strands of double-stranded DNA at different positions leaving overhangs of single-stranded DNA. Two pieces of DNA may be rejoined if their terminal overhangs are complementary. Complements are referred to as 'sticky ends'. Using these operations, fragments of DNA may be inserted or deleted from the DNA.

[attachment=12707]
DNA Computing
Abstract— An overview and categorization of existing research in DNA based computation, the possible advantages that different models have over conventional computational methods, and potential applications that might emerge from, or serve to motivate, the creation of a working Bimolecular Computer. The emerging paradigms of DNA based (or bimolecular) computation has yet to find a practical use, despite many possible advantages over existing computational methods. Possible applications are discussed for different models of DNA computation as well as their relative viability.
DNA computing has a great deal of advantage over conventional silicon-based computing. DNA computers can store billions of times more data than personal computer. DNA computers have the ability to work in a massively parallel fashion, performing many calculations simultaneously. DNA molecules that provide the input can also provide all the necessary operational energy.
Computer scientists are joining forces with molecular biologists and chemists to explore the potential for computation using information carrying biological polymers such as nucleic acids (DNA and RNA). "DNA computing” is a subset of molecular computing. "The key feature of DNA for computing is its information content.
DNA computing is in its infancy, and its implications are only beginning to be explored. But it could transform the future of computers, especially in pharmaceutical and biomedical Applications.
I. INTRODUCTION
DNA is the major information storage molecule in living cells, and billions of years of evolution have tested and refined both this wonderful informational molecule and highly specific enzymes that can either duplicate the information in DNA molecules or transmit this information to other DNA molecules.
Instead of using electrical impulses to represent bits of information, the DNA computer uses the chemical properties of these molecules by examining the patterns of combination or growth of the molecules or strings. DNA can do this through the manufacture of enzymes, which are biological catalysts that could be called the 'software' used to execute the desired calculation.
A. Structure of DNA
All organisms on this planet are made of the same type of genetic blueprint, which bind us together. Within the cells of any organism is a substance called Deoxyribonucleic Acid (DNA), which is a double-stranded helix of nucleotides, which carries the genetic information of a cell. 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 letters A (Adenine), T (Thymine), C (Cytosine) and G (Guanine).
Fig 1.Graphical representation of inherent bonding properties of DNA Fig 2.Illustration of double helix shape of DNA.
The bases (nucleotides) are spaced every 0.35 nanometers along the DNA molecule, giving it a remarkable data density of nearly 18Mbits per inch. These nucleotides will only combine in such a way that C always pairs with G and T always pairs with A. This complementarily makes DNA a unique data structure for computation and can be exploited in many ways.
The idea of using DNA to store and process information took off in the year 1994 when Leonard Adleman, a computer scientist at the University of Southern California, came to the conclusion that DNA had computational potential. Adleman caused an avalanche in the fields of biology; mathematics and computers by solving a problem called the Directed Hamiltonian Path problem or sometimes referred to as the Travelling Salesman Problem.
DNA computers use deoxyribonucleic acids--A (adenine), C (cytosine), G (guanine) and T (thymine)--as the memory units and recombinant DNA techniques already in existence carry out the fundamental operations. In a DNA computer, computation takes place in test tubes or on a glass slide coated in 24K gold. The input and output are both strands of DNA, whose genetic sequences encode certain information. A program on a DNA computer is executed as a series of biochemical operations, which have the effect of synthesizing, extracting, modifying and cloning the DNA strands.
The only fundamental difference between conventional computers and DNA computers is the capacity of memory units: electronic computers have two positions (on or off), whereas DNA has four (C, G, A or T). Many restriction enzymes cut the two strands of double-stranded DNA at different positions leaving overhangs of single-stranded DNA. Two pieces of DNA may be rejoined if their terminal overhangs are complementary.
DNA represents information as a pattern of molecules on a strand. Each strand represents one possible answer. In each experiment, the DNA is tailored so that all conceivable answers to a particular problem are included. Researchers then subject all the molecules to precise chemical reactions that imitate the computational abilities of a traditional computer. Because molecules that make up DNA bind together in predictable ways, it gives a powerful "search" function. If the experiment works, the DNA computer weeds out all the wrong answers, leaving one molecule or more with the right answer. All these molecules can work together at once, so you could theoretically have 10 trillion calculations going on at the same time in very little space.
II. IMPLEMENTATION
DNA computing is a field that holds the promise of ultra-dense systems that pack megabytes of information into devices the size of a silicon transistor. Each molecule of DNA is roughly equivalent to a little computer chip. Conventional computers represent information in terms of 0's and 1's, physically expressed in terms of the flow of electrons through logical circuits, whereas DNA computers represent information in terms of the chemical units of DNA. Computing with an ordinary computer is done with a program that instructs electrons to travel on particular paths; with a DNA computer, computation requires synthesizing particular sequences of DNA and letting them react in a test tube or on a glass plate. In a scheme devised by Richard Lipton, the logical command "and" is performed by separating DNA strands according to their sequences, and the command "or" is done by pouring together DNA solutions containing specific sequences, merging.
By forcing DNA molecules to generate different chemical states, which can then be examined to determine an answer to a problem by combination of molecules into strands or the separation of strands, the answer is obtained.
Most of the possible answers are incorrect, but one or a few may be correct, and the computer's task is to check each of them and remove the incorrect ones using restrictive enzymes. The DNA computer does that by subjecting all of the strands simultaneously to a series of chemical reactions that mimic the mathematical computations an electronic computer would perform on each possible answer. When the chemical reactions are complete, researchers analyze the strands to find the answer -- for instance, by locating the longest or the shortest strand and decoding it to determine what answer it represents.
Computers based on molecules like DNA will not have vonNeumann architecture, but instead function best in parallel processing applications. They are considered promising for problems that can have multiple computations going on at the same time. Say for instance, all branches of a search tree could be searched at once in a molecular system while vonNeumann systems must explore each possible path in some sequence.
Information is stored in DNA as CG or AT base pairs with maximum information density of 2bits per DNA base location. Information on a solid surface is stored in a NON-ADDRESSED array of DNA words (W) of a fixed length (16 mers).
DNA Words are linked together to form large combinatorial sets of molecules.DNA computers are massively parallel, while electronic computers would require additional hardware, DNA computers just need more DNA. This could make the DNA computer more efficient, as well as more easily programmable.
A. How much information cam they store and process
Nucleic Acids are used because of density, efficiency and speed. DNA molecules can store far more information than any existing computer memory chip. This means that DNA computing is a far denser packing of molecular information compared with silicon-based computers. A single bacterium cell measures just a micron square - about the same size as a single silicon transistor - but holds more than a megabyte of DNA memory and has all the computational structures to sense and respond to its environment. To try to put this in some understandable perspective, it has been estimated that a gram of DNA can hold as much information as a trillion CDs.
So DNA molecules would be like mega-memory. In a biochemical reaction hundreds of trillions of DNA molecules can operate in parallel. DNA computers could store a bit, 0 or 1, of data in one cubic nanometer, one trillionth the size of the conventional computer's electronic storage. Thus a DNA computer could store massive quantities of information in the space a standard computer would use to store much less. A pound of DNA could contain more computer memory than all the electronic computers ever made. It would be about twice as fast as the fastest supercomputer, performing more than 2,000 instructions per second. DNA computers also require miniscule amounts of energy to perform. Because the biochemical operations involved are subject to errors and are often slow, rigorous tests of the accuracy and further technological development are needed.
B. what about efficiency
In both the solid-surface glass-plate approach and the test tube approach, each DNA strand represents one possible answer to the problem that the computer is trying to solve. The strands have been synthesized by combining the building blocks of DNA, called nucleotides, with one another, using techniques developed for biotechnology. The set of DNA strands is manufactured so that all conceivable answers are included. Because a set of strands is tailored to a specific problem, a new set would have to be made for each new problem.
Most electronic computers operate linearly--they manipulate one block of data after another--biochemical reactions are highly in parallel: a single step of biochemical operations can be set up so that it affects trillions of DNA strands. While a DNA computer takes much longer than a normal computer to perform each individual calculation, it performs an enormous number of operations at a time and requires less energy and space than normal computers.
Obviously if you want to perform one calculation at a time, DNA computers are not a viable option. When Adleman derived an optimal solution to a seven-city traveling-salesman problem, it took approximately one week. Unfortunately, you can solve the same problem on a piece of paper in about an hour - or by a digital computer in a few seconds. But when the number of cities is increased to just 70, the problem becomes intractable for even a 1,000-Mips supercomputer.
Adleman, now considered the father of DNA computing, is a professor at the University of Southern California and spawned the field with his paper, "Molecular Computation of Solutions of Combinatorial Problems." Since then, Adleman has demonstrated how the massive parallelism of a trillion DNA strands can simultaneously attack different aspects of a computation to crack even the toughest combinatorial problems, such as the government's supposedly uncrackable Data Encryption Standard.

Presented by:
CHETAN KUMAR D

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DNA COMPUTING
Introduction
Ever wondered where we would find the new material needed to build the next generation of microprocessors????
HUMAN BODY (including yours!)…….DNA computing.
“Computation using DNA” but not “computation on DNA”
Initiated in 1994 by an article written by Dr. Adleman on solving TSP problem using DNA.
DNA itself does not carry out any computation. It rather acts as a massive memory.
BUT, the way complementary bases react with each other can be used to compute things.
Proposed by Adelman in 1994
Uniqueness of DNA
Why is DNA a Unique Computational Element???
Extremely dense information storage.
Enormous parallelism.
Extraordinary energy efficiency.
Dense Information Storage
How Dense is the Information Storage?
with bases spaced at 0.35 nm along DNA, data density is over a million Gbits/inch compared to 7 Gbits/inch in typical high performance HDD.
Check this out………..
How enormous is the parallelism?
A test tube of DNA can contain trillions of strands. Each operation on a test tube of DNA is carried out on all strands in the tube in parallel !
Check this out……. We Typically use
How extraordinary is the energy efficiency?
Adleman figured his computer was running
2 x 1019 operations per joule.
Biochemistry Basics
Extraction
given a test tube T and a strand s, it is possible to extract all the strands in T that contain s as a subsequence, and to separate them from those that do not contain it.
Annealing
Polymerase Chain Reaction
Gel Electrophoresis
Used to measure the length of a DNA molecule.
Based on the fact that DNA molecules are –ve ly charged.
DNA Microarrays are small, solid supports onto which the sequences from thousands of different genes are immobilized, or attached, at fixed locations.
The supports themselves are usually glass microscope slides, the size of two side-by-side pinky fingers, but can also be silicon chips or nylon membranes.
The DNA is printed, spotted, or actually synthesized directly onto the support. With the aid of a computer, the amount of mRNA bound to the spots on the microarray is precisely measured, generating a profile of gene expression in the cell.
The smallest programmable DNA computer was developed at Weizmann Institute in Israel by Prof. Ehud Shapiro last year
It uses enzymes as a program that processes on on the input data (DNA molecules).
http://weizmann.ac.il/mathusers/lbn/new_...gical.html
Adleman’s Experiment
Discover magazine published an article in comic strip format about Leonard Adleman's discovery of DNA computation. Not only entertaining, but also the most understandable explanation of molecular computation I have Ever seen.
THE FUTURE!
Algorithm used by Adleman for the traveling salesman problem was simple. As technology becomes more refined, more efficient algorithms may be discovered.
DNA Manipulation technology has rapidly improved in recent years, and future advances may make DNA computers more efficient.
The University of Wisconsin is experimenting with chip-based DNA computers.
DNA computers are unlikely to feature word processing, emailing and solitaire programs.
Instead, their powerful computing power will be used for areas of encryption, genetic programming, language systems, and algorithms or by airlines wanting to map more efficient routes. Hence better applicable in only some promising areas.

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