MACHINE LEARNING TECHNIQUES BASED DNA SEQUENCE ALIGNMENT: A SYSTEMATIC LITERATURE REVIEW

Abstract

The massive volume of organic information, the conventional software engineering procedures and calculations neglect to take care of complex natural issues of this present reality. In any case, present day computational methodologies, for example, AI can address the restrictions of the customary strategies. AI has assumed a significant job in building up Bioinformatics as a field in its own in the course of the most recent 30 years. For solving the complex problems of biological data we use Machine Learning Techniques for Deoxyribonucleic Acid (DNA) Sequence Alignment data. We present a Systematic Literature Review Protocol (SLRP) of DNA sequence alignment using machine learning technique. This proposition played out an archived arrangement of explicit techniques which are useful to utilize the Systematic Literature Review (SLR). The anticipated outcomes of this survey recognize the DNA Sequence Alignment utilizing Machine Learning Techniques, investigate issues, order the issues, characterize the significant qualities and furthermore talk about the general attributes. The normal advantages of this investigation in future will be Systematic best in class of machine learning method in bioinformatics that will be supportive for new Researchers to represent DNA succession arrangement utilizing machine learning procedures.