Innovative Computational Moulding Approach for Genomics

In the modern era, deep learning studies have been undertaken in different fields of research such as speech recognition, image type, autonomous use, and language processing. The objective of the project is to examine the use of genomics in deep learning. The study focuses on literature using DL models. The in-depth study showed a significant improvement in overall performance in compound classification and regression problems, wherever the complicated form of large-dimensional statistics is difficult to exploit to take advantage of convolutional ML algorithms. In the field of biology, deep learning applications are gaining popularity in predicting the shape and feature of genomic elements, together with enhancers, promoters, or gene expression levels.. In this review article, we generally tend to expose the most used deep learning architectures for the genomic domain. Then we supplied a concise overview of deep learning applications in genomics and artificial biology on the ranges of DNA, RNA, and protein. Finally, we affirmed the prevailing difficult situations and emerging perspective of deep learning in genomics.