الفهرس | Only 14 pages are availabe for public view |
Abstract DNA Computing is the execution of calculations utilizing natural particles, and DNA particularly, rather than silicon. DNA computing field first emerged for solving Hamiltonian Path Problem (HPP), as a famous example for NP Complete problem, utilizing techniques of recombinant DNA. The upsides of DNA over silicon consist of three advantages. First, huge parallelism where the calculations can be achieved simultaneously. Second, size where DNA Computers are much smaller. Third, storage density where a whole lot more data can be put away in a smaller space. Nevertheless, there’s two problems in DNA computing. First, the error susceptibility of biochemical operations. Second, DNA computing suffers from exponential space problem. The motivation of this research study is to overcome these two drawbacks of DNA computing. In this thesis, the authors proposes a DNA computational model that is robust and can solve NP problems in polynomial time and PSPACE problems in polynomial space. Also, in this thesis, the authors proposes “Visual DNA” which is a software that can represent biochemical operations in DNA computing. It can be used to make sure of the results of the biochemical operations before doing in vitro experiments. Also, we showed in the thesis that the applicability of implementing evolutionary and genetic algorithms with DNA computing in breaki ng the two drawbacks mentioned before. |