04-02-2012, 10:37 PM
i need an information,ppt,pdf about DNA computing!
04-02-2012, 10:37 PM
i need an information,ppt,pdf about DNA computing!
06-02-2012, 12:26 PM
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23-11-2012, 04:10 PM
DNA Computing
DNA Computing.docx (Size: 126.74 KB / Downloads: 36) INTRODUCTION Today’s silicon-based microprocessors are manufactured under the strictest of conditions. Researchers are building what they hope will be some of tomorrow’s computers in environments that are far from sterile—beakers, test tubes and petri dishes full of bacteria. Simply put, these scientists seek to create cells that can compute, endowed with “intelligent” genes that can add numbers, store the results in some kind of memory bank, keep time and perhaps one day even execute simple programs. All of these operations sound like what today’s computers do. Yet these biological systems could open up a whole different realm of computing. “It is a mistake to envision the kind of computation that we are envisioning for living cells as being a replacement for the kinds of computers that we have now,” says Tom Knight, a researcher at the MIT Artificial Intelligence Laboratory and one of the leaders in the biological computing movement. First of all, it’s extremely cost-effective. Once you’ve programmed a single cell, you can grow billions more for the cost of simple nutrient solutions and a lab technician’s time. In the second place, biological computers might ultimately be far more reliable than computers built from wires and silicon, for the same reason that our brains can survive the death of millions of cells and still function whereas your Pentium-powered PC will seize up if you cut one wire. 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. INFORMATION ABOUT DNA We have heard the term DNA(Deoxyribonucleic acid) 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). HOW DNA COMPUTERS WILL WORK 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: Similarities Transformation of Data Both DNA computers and electronic computers use Boolean logic (AND, OR, NAND, NOR) to transform data. 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. For example, the logical statement "X or Y" is true if X is true or if Y is true. To simulate that, the scientists would pour the DNA strands corresponding to "X" together with those corresponding to "Y." Manipulation of Data Electronic computers and DNA computers both store information in strings, which are manipulated to do processes. Vast quantities of information can be stored in a test tube. The information could be encoded into DNA sequences and the DNA could be stored. To retrieve data, it would only be necessary to search for a small part of it - a keyword, for example – by adding a DNA strand designed so that its sequence sticks to the key word wherever it appears on the DNA. Computation Ability All computers manipulate data by addition and subtraction. A DNA computer should be able to solve a satisfiability problem with 70 variables and 1,000 AND-OR connections. To solve it, assign various DNA sequences to represent 0’s and 1’s at the various positions of a 70 digit binary number. Vast numbers of these sequences would be mixed together, generating longer molecules corresponding to every possible 70-digit sequence. Differences Size Conventional computers are about 1 square foot for the desktop and another square foot for the monitor. One new proposal is for a memory bank containing more than a pound of DNA molecules suspended in about 1,000 quarts of fluid, in a bank about a yard square. Such a bank would be more capacious than all the memories of all the computers ever made. The first ever electronic computer (Eniac) took up a large room whereas the first DNA computer (Adleman) was 100 micro liters. Adleman dubbed his DNA computer the TT-100, for test tube filled with 100 micro liters, or about one-fiftieth of a teaspoon of fluid, which is all it took for the reactions to occur. 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). DRAWBACKS Occasionally Slow The speed of each process in DNA Computing is still an open issue until now. In 1994, Adleman’s experiment took still a long time to perform. The entire experiment took Adleman 7 days of lab work. Adleman asserts that the time required for an entire computation should grow linearly with the size of the graph. This is true as long as the creation of each edge does not require a separate process. Hydrolysis The DNA molecules can fracture. Over the six months you're computing, your DNA system is gradually turning to water. DNA molecules can break – meaning a DNA molecule, which was part of your computer, is fracture by time. DNA can deteriorate. As time goes by, your DNA computer may start to dissolve. DNA can get damaged as it waits around in solutions and the manipulations of DNA are prone to error. Some interesting studies have been done on the reusability of genetic material in more experiments, a result is that it is not an easy task recovering DNA and utilizing it again. Information Untransmittable The model of the DNA computer is concerned as a highly parallel computer, with each DNA molecule acting as a separate process. In a standard multiprocessor connection-bus transmit information from one processor to the next. But the problem of transmitting information from one molecule to another in a DNA computer has not yet to be solved. Current DNA algorithms compute successfully without passing any information, but this limits their flexibility. 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. |
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