Author(s) :

B Aditya.

Volume/Issue :

Abstract :

Genomic research is an essential component of modern medicine, providing critical insights into the genetic underpinnings of diseases and facilitating the development of personalized treatment approaches. However, the vast and complex nature of genomic data presents significant challenges for traditional data analysis methods. This project explores the application of deep learning models to big genomic data to address these challenges and enhance the accuracy of genomic predictions. Deep learning, with its ability to process large volumes of high-dimensional data, has shown great promise in various fields, including genomics, by automating the extraction of relevant patterns and features from genomic sequences.This project investigates the use of deep learning techniques such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Autoencoders in the analysis of genomic datasets.

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