22-11-2012, 02:25 PM
Report on DNA Computing
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INTRODUCTION
DNA Computer can store billions of times more information than 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 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 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 travelling 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 fewminutes 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.
INFORMATION ABOUT DNA
“Deoxyribonucleic acid” The molecules inside cells that carry genetic information and pass it from one generation to the next See mitosis, chromosomes.
We have heard the term DNA a million times. You know that DNA is something inside cells .We knows that each and every one looks different and this is because of they are having different DNA.
Have you ever wondered how the DNA in ONE egg cell and ONE sperm cell can produce a whole human being different from any other? How does DNA direct a cell's activities? Why do mutations in DNA cause such trouble (or have a positive effect)? How does a cell in your kidney "know" that it's a kidney cell as opposed to a brain cell or a skin cell or a cell in your eye? How can all the information needed to regulate the cell's activities be stuffed into a tiny nucleus?
A basic tenet is that all organisms on this planet, however complex they may be perceived to be, are made of the same type of genetic blueprint .The mode by which that blue print is coded is the factor that decides our physical makeup-from colour of our eyes to whatever we are human.
STRUCTUTE OF DNA
This structure has two helical chains each coiled round the same axis. We have made the usual chemical assumptions, namely, that each chain consists of phosphate diester groups joining ß-D-deoxyribofuranose residues with 3',5' linkages. The two chains (but not their bases) are related by a dyad perpendicular to the fibre axis. Both chains follow right- handed helices, but owing to the dyad the sequences of the atoms in the two chains run in opposite directions. The novel feature of the structure is the manner in which the two chains are held together by the purine and pyrimidine bases.
If it is assumed that the bases only occur in the structure in the most plausible tautomeric forms (that is, with the keto rather than the enol configurations) it is found that only specific pairs of bases can bond together. These pairs are: adenine (purine) with thymine (pyrimidine), and guanine (purine) with cytosine (pyrimidine).
In other words, if an adenine forms one member of a pair, on either chain, then on these assumptions the other member must be thymine ; similarly for guanine and cytosine. The sequence of bases on a single chain does not appear to be restricted in any way. However, if only specific pairs of bases can be formed, it follows that if the sequence of bases on one chain is given, then the sequence on the other chain isautomatically determined.
Strands of DNA are long polymers of millions of linked nucleotides. These nucleotides consist of one of four nitrogen bases, a five carbon sugar and a phosphate group. The nucleotides that make up these polymers are named alter, the nitrogen bases that comprise it, namely, Adenine (A), Cytosine ©, Guanine (G), and Thymine (T). These nucleotides only combine in such a way that C always pairs with G, and T always pairs with A. These two strands of a DNA molecule are anti-parallel in that each strand runs in a opposite direction. Here below figure shows two strands of DNA and the bonding principles of the four types of nucleotides.
A Fledgling Technology :
DNA computers can't be found at your local electronics store yet. The technology is still in development, and didn't even exist as a concept a decade ago. In 1994, Leonard Adleman introduced the idea of using DNA to solve complex mathematical problems. Adleman, a 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 Watson, who co-discovered the structure of DNA in 1953. In fact, DNA is very similar to a computer hard drive in how it stores permanent information about your genes.
Adleman is often called the inventor of DNA computers. His article in a 1994 issue of the 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 number of cities, going through each city only once. As you add more cities to the problem, the problem becomes more difficult. Adleman chose to find the shortest route between seven cities.
You could probably draw this problem out on paper and come to a solution faster than Adleman did using his DNA test-tube computer. Here are the steps taken in the Adleman DNA computer experiment:
Strands of DNA represent the seven cities. In genes, genetic coding is represented by the letters A, T, C and G. Some sequence of these four letters represented each city and possible flight path. These molecules are then mixed in a test tube, with some of these DNA strands sticking together. A chain of these strands represents a possible answer. Within a few seconds, all of the possible combinations of DNA strands, which represent answers, are created in the test tube. Adleman eliminates the wrong molecules through chemical reactions, which leaves behind only the flight paths that connect all seven cities.
Parallelism:-
Electronic computers typically handle operations in a sequential manner. 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; I fetch an instruction and the appropriate data from main memory, and it executes the instruction. It does these many, many times in a row, really, really fast. The great Richard Feynman, in his Lectures on Computation, summed up von Neumann computers by saying, "the inside of a computer is as dumb as hell, but it goes like mad!" DNA computers, however, are non-von Neuman, stochastic machines that approach computation in a different way from ordinary computers for the purpose of solving a different class of problems. 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
Methods of Calculation:-
By synthesizing particular sequences of DNA, DNA computers carry out calculations. Conventional computers represent information physically expressed in terms of the flow of electrons through logical circuits. Builders of DNA computers represent information in terms of the chemical units of DNA. Calculating with an ordinary computer is done with a program that instructs electrons to travel on particular paths; with a DNA computer, calculation requires synthesizing particular sequences of DNA and letting them react in a test tube . As it is, the basic manipulations used for DNA Computation include Anneal, Melt, Ligate, Polymerase Extension, Cut, Destroy, Merge, Separate by Length which can also be combined to high level manipulations such as Amplify, Separate by Subsequence, Append, Mark, Unmark. And the most famous example of a higher-level manipulation is the polymerase chain reaction (PCR).
Conclusion
This is becoming one of the most exciting fields. I’ll conclude this paper by just sharing a vision for the future in which a single drop of water holds a veritable army of living robots; in which people download software updates not for their computers, but for their bacteria; and in which specially programmed cells course through a person's arteries, monitoring blood sugar concentrations and keeping an eye out for cholesterol build-ups.
These scenarios still belong to the realm of science fiction—but implanting computer programs into living creatures may not be far away. In the past few years , scientists have taken the first steps towards creating a host of cellular robots that are programmed to carry out tasks such as detecting and cleaning up environmental pollutants, tracking down cancer cells in a body, and manufacturing antibiotics or molecular-scale electronic components. These researchers have imported notions of electrical engineering—digital logic, memory, and oscillators—into the realm of biology.