DNA Computing and Implementations

Abstract

DNA Computing aims to harness the molecules at the Nano level for computational purpose. DNA Computing features high data density and massive storage capability therefore, its approach can be used to solve various combinatorial Problems like solving Non Deterministic Problems (i.e. NP- Complete and NP-Hard). This Molecular Level Computational involve input and output both in the molecule form. Since DNA has already been explored as an exquisite material and is a fundamental block for manufacturing large scale Nano mechanical devices. DNA Computing is an approach towards the Biomolecular Computation where the aim is not only to process the information but also to transfer it to other molecular structures for utilization. DNA Computing is slower when an individual DNA Computes in compare to silica based chips. Its Efficiently and throughput increases as the number of DNA increase. DNA provides the possibility of massive parallelism. Starting with the Introduction about the DNA Structure, followed up by DNA Computers, this paper will discuss some recent advancements and challenges of DNA Computing. We will also discuss the possible future scope and implementation as well how the Artificial Intelligence approach can be used with DNA Based Computers to achieve a better and efficient Machine Learning.