Application of Deep Learning in Biological Big Data Analysis

View Sample PDF

Author(s): Rohit Shukla (Department of Biotechnology and Bioinformatics, Jaypee University of Information Technology, India), Arvind Kumar Yadav (Department of Biotechnology and Bioinformatics, Jaypee University of Information Technology, India)and Tiratha Raj Singh (Department of Biotechnology and Bioinformatics and Centre for Excellence in Healthcare technologies and Informatics (CEHTI), Jaypee University of Information Technology, India)
Copyright: 2024
Pages: 26
Source title: Research Anthology on Bioinformatics, Genomics, and Computational Biology
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/979-8-3693-3026-5.ch011

Keywords: Bioinformatics / Medical Information Science Reference / Medicine & Healthcare

Purchase

View Application of Deep Learning in Biological Big Data Analysis on the publisher's website for pricing and purchasing information.

Abstract

The meaningful data extraction from the biological big data or omics data is a remaining challenge in bioinformatics. The deep learning methods, which can be used for the prediction of hidden information from the biological data, are widely used in the industry and academia. The authors have discussed the similarity and differences in the widely utilized models in deep learning studies. They first discussed the basic structure of various models followed by their applications in biological perspective. They have also discussed the suggestions and limitations of deep learning. They expect that this chapter can serve as significant perspective for continuous development of its theory, algorithm, and application in the established bioinformatics domain.

The IRMA Community

Research IRM

Application of Deep Learning in Biological Big Data Analysis

Purchase

Abstract

Related Content

IRMA Sponsors