DNA COMPUTER-The Future of Computing
DNA computing is a form of computing which uses DNA and biochemistry and molecular biology instead of the traditional silicon based computer technologies.DNA computing or more generally molecular computing is a fast developing interdisciplinary area.
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 ...view middle of the document...
So Atlanta’s last name is GCAG,whereas Boston’s ﬁrst name is TCGG.Next, I gave each nonstop ﬂight a DNA“ﬂight number ,” obtained by concatenating the last name of the city of origin with the ﬁrst name of the city of desti-nation. In the example, the Atlanta-to-Boston ﬂight number becomes GCAGTCGG.Recall that each strand of DNA has its Watson-Crick complement. Thus, each city has its complementary DNA name. Atlanta’s complementary name becomes, for instance, TGAACGTC.After working out these encodings, I had the complementary DNA city names and the DNA ﬂight numbers synthesized.
(As it turned out, the DNA city names themselves were largely unnecessary.) I took a pinch (about 1014 molecules) of each of the different sequences and put them into a common test tube. To begin the computation, I simply added water—plus ligase, salt and a few other ingredients to approximate the conditions inside a cell. Altogether only about one ﬁftieth of a teaspoon of solution was used. Within about one second, I held the answer to the Hamiltonian Path Problem in my hand.To see how, consider what transpires in the tube.
For example, the Atlanta-to-Boston ﬂight number (GCAGTCGG)and the complementary name of Boston(AGCCTGAC) might meet by chance.By design, the former sequence ends with TCGG, and the latter starts with AGCC. Because these sequences are complementary, they will stick together . If the resulting complex now encounters the Boston-to-Chicago ﬂight number (ACTGGGCT), it, too, will join the complex because the end of the former (TGAC) is complementary to the beginning of the latter (ACTG).In this manner,complexes will grow in length, with DNA ﬂight numbers splinted together by complementary DNA city names. The ligase in the mixture will then permanently concatenate the chains of DNA ﬂight numbers. Hence,the test tube contains molecules that encode random paths through the different cities (as required in the ﬁrst step of the algorithm).Because I began with such a large number of DNA molecules and the problem contained just a handful of cities, there was a virtual certainty that at least one of the molecules formed would encode the Hamiltonian path. It was amazing to think that the solution to a mathematical problem could be stored in a single molecule! Notice also that all the paths were created at once by the simultaneous interactions of literally hundreds of trillions of molecules. This biochemical reaction represents enormous parallel processing.
For the map, there is only one Hamiltonian path, and it goes through Atlanta, Boston, Chicago and Detroit, in that order.Thus,the molecule encoding the solution will have the sequence GCAGTCGGACTGGGCTATGTCCGA.Unfortunately, although I held the solution in my hand, I also held about 100 trillion molecules that encoded paths that were not Hamiltonian. These had
to be eliminated. To weed out molecules that did not both begin with the start...