Improving DNA Computing through CRISPR based Model and Visual DNA Tool | ||||
| Mansoura Journal for Computer and Information Sciences | ||||
| Volume 14, Issue 2, December 2018, Page 47-56 PDF (637.47 K) | ||||
| Document Type: Original Research Articles. | ||||
| DOI: 10.21608/mjcis.2018.312010 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| A. M. El-Edkawy; M. A. El-Dosuky; Taher Hamza | ||||
| Computer Science Department, Faculty of Computers and Information Mansoura University Egypt | ||||
| Abstract | ||||
| Since the advent of DNA computing field; there’s debate about its ability to solve hard computational problems. A way to deal with the debate is to design a computational model for DNA computing and then studying its complexity power. The main contribution of this paper is to propose a DNA computing model that presents a usage of CRISPR in DNA computing field. The model has three basic operations which are merge, CRISPR and detect. The model is argued to be robust, as the three operations are robust, and to be the minimum model for DNA computing in terms of the number of operations. The proposed model has corresponded with a model inspired from the evolution of DNA sequences called Accepting Hybrid Network of Evolutionary Processors (AHNEPs). Based on that correspondence, the proposed model can be used to solve NP problems in polynomial time and PSPACE problems in polynomial space. The model is used to solve, the NP problem, the Hamiltonian Path Problem (HPP) in linear time. The limitations of DNA computing area could be avoided within the model. Also, the study presents “Visual DNA” which is a software that can simulate biochemical operations in DNA computing. Also, the software can make analysis for DNA sequences. So this simulation software will offer a useful tool for the DNA computing implementation because it will help in the analysis of input DNA sequences and in the prediction of output DNA sequences which would be helpful to avoid errors during the experimental process | ||||
| Keywords | ||||
| DNA Computing; Theoretical Computer Science; Computability Theory | ||||
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