Applications of Deep Learning in Genomics
Published on 12. November 2025
268 pages
978-1-040-54479-2 (ISBN)
Description
The objective of the book is to use advanced deep learning techniques to unlock the complexities of genomic data. It reveals hidden and unknown patterns, to improve our understanding the role of genetics in diseases, speeding up drug discovery processes, illuminating evolutionary trajectories, and dealing with the challenges posed by large genomic datasets. It also addresses ethical concerns, provides real-world applications, reviews future frontiers like as quantum computing and multi-omics integration, and presents a thorough picture of the genetic environment. Overall, the book aims to enhance our ability to use genomics for more precise forecasts, personalised therapies, and a better understanding of the underlying genetic fabric that defines life.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Illustrations
19 Tables, black and white; 9 Line drawings, color; 22 Line drawings, black and white; 2 Halftones, color; 11 Illustrations, color; 22 Illustrations, black and white
File size
11,38 MB
ISBN-13
978-1-040-54479-2 (9781040544792)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Bipin Kumar Rai | Rupa Rani | Gautam Kumar
Applications of Deep Learning in Genomics
Book
11/2025
1st Edition
CRC Press
€169.50
Shipment within 10-20 days
Persons
Bipin Kumar Rai is a Professor in the Department of Computer Science & Engineering, Dayanand Sagar University, Bangalore. He has a PhD from Banasthali University, Rajasthan and M. Tech (CSE) from RGPV Bhopal & B. Tech (CSE) from UPTU Lucknow, India. Dr. Bipin Kumar Rai has 20+ years teaching experience in renowned institutions. He has been actively involved in various academic and administrative roles. His interests include Information security, ML and blockchain. He has published 50+ research papers in WoS/Scopus indexed journals/conferences, 5 books and 5 patents. He has worked as an Editor/Reviewer of several SCI/Scopus indexed journals and as a session chair/TPC member in several conferences.
Rupa Rani is an Assistant Professor in the Department of CSE at AKG Engineering College, Ghaziabad (India). She has a PhD in Computer Science & Engineering from Banasthali Vidyapith, Rajasthan, and has a MTech in Computer Engineering. She published 20+ research papers indexed in WoS/Scopus journals/conferences. Her research interests include data science, AI, ML and cyber security.
Gautam Kumar is an Associate Professor at Manipal University Jaipur, India with the School of Computer Science and Engineering. He has a PhD degree in CSE from Jaypee University of Information Technology, India, and has MTech from RTU, Rajasthan & B.E. from RGPV, Bhopal, MP. His research interests cover cryptography, information security, algorithms, design and analysis of algorithms. He has published 50+ journals/conferences papers indexed in SCI/Scopus, 3 published books and 5 published patents.
Rupa Rani is an Assistant Professor in the Department of CSE at AKG Engineering College, Ghaziabad (India). She has a PhD in Computer Science & Engineering from Banasthali Vidyapith, Rajasthan, and has a MTech in Computer Engineering. She published 20+ research papers indexed in WoS/Scopus journals/conferences. Her research interests include data science, AI, ML and cyber security.
Gautam Kumar is an Associate Professor at Manipal University Jaipur, India with the School of Computer Science and Engineering. He has a PhD degree in CSE from Jaypee University of Information Technology, India, and has MTech from RTU, Rajasthan & B.E. from RGPV, Bhopal, MP. His research interests cover cryptography, information security, algorithms, design and analysis of algorithms. He has published 50+ journals/conferences papers indexed in SCI/Scopus, 3 published books and 5 published patents.
Content
1) Introduction: Genomic Landscape & Deep Learning Rise
2) Unraveling Genetic Code: Basics & Deep Learning Role
3) Genomic Data Deluge: Handling Big Data with DL
4) Mining Biological Gold: DL in Disease, Drug, Evolution Insights
5) Navigating Genome: Neural Networks, Transfer Learning, Explainability
6) Ethical Considerations: Privacy, Fairness, Bias in Genomic Data
7) Blockchain Integration in Genomic Deep Learning: Securing, Validating, and Sharing Genetic Insights
8) Future Horizons: Multi-Omics, Quantum Computing, Collaboration
9) Case Studies: Real-world Apps, Lessons
10) Challenges & Opportunities: Technical Hurdles, Robust Models
11) Conclusion: Recap & Genomic Frontier Ahead
2) Unraveling Genetic Code: Basics & Deep Learning Role
3) Genomic Data Deluge: Handling Big Data with DL
4) Mining Biological Gold: DL in Disease, Drug, Evolution Insights
5) Navigating Genome: Neural Networks, Transfer Learning, Explainability
6) Ethical Considerations: Privacy, Fairness, Bias in Genomic Data
7) Blockchain Integration in Genomic Deep Learning: Securing, Validating, and Sharing Genetic Insights
8) Future Horizons: Multi-Omics, Quantum Computing, Collaboration
9) Case Studies: Real-world Apps, Lessons
10) Challenges & Opportunities: Technical Hurdles, Robust Models
11) Conclusion: Recap & Genomic Frontier Ahead
