PAPER PRESENTATION

Here is the summarised abstract of a paper presentation i made on DNA COMPUTATION

What it is?. DNA computing is a form of computing which uses DNA and molecular biology, instead of the traditional silicon-based computer
The Origin- Adleman was struck by how how a living enzyme "reads" DNA much the same way computer pioneer 1936is was calculated how a machine could read data.
If you look inside the cell you find a bunch of amazing little tools,The cell is a treasure chest. ?
Adleman used his computer to solve the classic problems there by drawing similarity between dna strand and the computer.For example -"traveling salesman" mathematical problem -- how a salesman can visit a given number of cities without passing through any city twice -- by exploiting the predictability of how DNA interacts. He generated thousands of random paths, in much the same way that a computer can sift through random numbers to break a code.
Advantages-
The primary advantage offered by most proposed models of DNA based computation is the ability to handle millions of operations in parallel. The massively parallel processing capabilities of DNA computers may give them the potential to find tractable solutions to otherwise intractable problems, as well as potentially speeding up large, but otherwise solvable, polynomial time problems requiring relatively few operations. The use of DNA to perform massive searching and related algorithms will be referred to as "classic" DNA computation for the purposes of this discussion. Proposed "classical" models of DNA computers derive their potential advantage over conventional computers from their ability to: Perform millions of operations simultaneously; Generate a complete set of potential solutions; Conduct large parallel searches; and Efficiently handle massive amounts of working memory. of optimal encoding techniques, and the ability to perform necessary bio-operations conveniently in vitro or in vivo.

. . Disadvantages-
Biologists are only now grasping the basics of how and why DNA unzips, recombines and sends and receives information. DNA is notoriously fragile and prone to transcription errors -- as the world's cancer rate thus a lot a work is still required for it to be success.
A limited amount of work has been directed at real-life applications and the practical feasibility of DNA computers. While the practical benefits of DNA based computational schemes are still questionable and the vast majority of work to date has been theoretical, there have been many allusions to
These models also have some of the following drawbacks: Each stage of parallel operations requires time measured in hours or days, with extensive human or mechanical intervention between steps; Generating solution sets, even for some relatively simple problems, may require impractically large amounts of memory; and Many empirical uncertainties, including those involving: actual error rates, the generation
The future-These realizations and others have tempered initial expectations that DNA would ultimately replace silicon chips. Still, researchers in this field believe they remain on the vanguard of a computational revolution. After all, a single gram of dried DNA, about the size of a half-inch sugar cube, can hold as much information as a trillion compact disk.