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INDEX 1) 2) INTRODUCTION TO BIOMOLECULAR COMPUTING HAMILTON PATH PROBLEM 4 5 2.1 Possible flight routes between seven cities________________________________6 2.2 Connecting Block___________________________________________________7 2.3 Double Helics______________________________________________________ 7 2.4 Long Chain________________________________________________________7 2.5 Different Colour___________________________________________________ 7 3) 4) 5) 6) 7) 8) 9) PROGRAMMING OF PROBLEM U
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  INDEX 1) INTRODUCTION TO BIOMOLECULAR COMPUTING 4 2) HAMILTON PATH PROBLEM   5 2.1 Possible flight routes between seven cities________________________________62.2 Connecting Block___________________________________________________72.3 Double Helics______________________________________________________ 72.4 Long Chain________________________________________________________72.5 Different Colour___________________________________________________ 7 3) PROGRAMMING OF PROBLEM USING DNA 8 4) WORKING OF DNA ______________________________________________10 5) APPLICATION 17 6) EFFICIENCY ___________________________________________________  21 7) ADVANTAGES-DISADVANTAGES 22 8) FUTURE 24 9) CONCLUSION ___________________________________________________ 2 9 1. INTRODUCTION TO BIO-MOLECULAR COMPUTING  Computer chip manufactures are furiously racing to make the nextmicroprocessor that will topple speed records. Sooner or later, though, thiscompetition is bound to hit a wall. Microprocessor made of silicon willeventually reach their limits of speed and miniaturization. Chip makers need anew material to produce faster computing speeds.You won’t believe where scientists have found the new material theyneed to build the next generation of microprocessors. Millions of naturalsupercomputers exist inside living organisms, including your living body. Theyare nothing else but Bio-Molecules itself. Especially DNA. DNA(deoxyribonucleic acid) molecules, the material our genes are made of, have thepotential to perform calculations many faster than the world’s most powerfulhuman-built computers. The other Bio-Molecules like Nucleotides,Nuclesoides, Saccharides, Lignin, Lipids, Amino acids… What is a DNA Computer? Research in the development of DNA computers is really only at itsbeginning stages, so a specific answer isn't yet available. But the general senseof such a computational device is to use the DNA molecule as a model for itsconstruction.Although the feasibility of molecular computers remains in doubt, thefield has opened new horizons and important new research problems, both for computer scientists and biologists. The computer scientist and mathematicianare looking for new models of computation to replace with acting in a test tube.The massive parallelism of DNA strands may help to deal withcomputational problems that are beyond the reach of ordinary digital computers-- not because the DNA strands are smarter, but because they can make manytries at once. It's the parallel nature of the beast. For the biologist, the 2  unexpected results in DNA computing indicate that models of DNA computerscould be significant for the study of important biological problems such asevolution. 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. Thetechnology is still in their development, and didn’t exist as concept before adecade. In 1994, LEONARD ADELMAN introduced the idea of using DNA tosolve complex mathematical problems. Adelman, computer scientist at theuniversity of Southern California, came to the conclusion that DNA hadcomputational potential after reading the book  “MOLECULAR BIOLOGYOF THE GENE” written by JAMES WASTON, who co-discovered thestructure of DNA in 1953.In fact, DNA is more similar to computer. DNA isvery similar to a computer hard drive in how it stores permanent informationabout your genes. 2. HAMILTON PATH PROBLEM Adelman is often called the inventor of the DNA computers. His article ina 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 isto find the shortest route between a numbers of cities, going through each city 3  only once. As you add more cities the problem becomes more difficult.Figure 2.1 shows a diagram of the Hamilton path problem. The objectiveis to find a path from start to end going through all the points only once. Thisproblem is difficult for the conventional (serial logic) computers because theytry must try each path one at a time. It is like having a whole bunch of keys andtrying to see which fits into the lock. Conventional computers are very good atmath, but poor at “key into lock” problems. DNA based computers can try allthe keys at the same time (massively parallel) and thus are very good at key intolock problems, but much slower at simple mathematical problems likemultiplication. The Hamilton path problem was chosen because every key-into-lock problem can be solved as a Hamilton Path Problem. Figure 2.1  Figure showing the possible flight routes between the seven cities. 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 concludewith the end city (G).3. Because the graph has 7 cities, keep only those paths with 7 cities. 4
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