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Potential Applications of Deep Learning in Bioinformatics Big Data Analysis - 2021

Potential Applications Of Deep Learning In Bioinformatics Big Data Analysis

Research Paper on Potential Applications Of Deep Learning In Bioinformatics Big Data Analysis

Research Area:  Machine Learning


Digital progresses in omics datasets particularly in the field of genomics and proteomics result in an exponential growth of sequence, molecular and image data. The analysis of such fast-growing and high-dimensional biological datasets is a challenging task with conventional analysis approaches. Extracting essential knowledge from such big omics data is as exciting and significant task in bioinformatics research. With the substantial progress of computational techniques and the improvement of biomolecular big data, modern machine learning method, such as deep learning appears as fruitful algorithms in current years to address such problems. Deep learning has attained great achievement in several fields for handling big datasets and for discovering hidden information and making correct predictions, and bioinformatics is no exception. In this review, potential applications of deep learning in bioinformatics research such as genomic sequence analysis, protein structure prediction, biomedical image processing and other omics data analyses have been presented.

Deep Learning
Big Data Analysis

Author(s) Name:  Jayakishan Meher

Journal name:  Advanced Deep Learning for Engineers and Scientists

Conferrence name:  

Publisher name:  Springer

DOI:  10.1007/978-3-030-66519-7_7

Volume Information:  pp 183–193