Deep Learning in Genetics and Genomics
Volume 1: Foundations and Introductory Applications
- 1st Edition - November 28, 2024
- Latest edition
- Editor: Khalid Raza
- Language: English
Deep Learning in Genetics and Genomics vol. 1, Foundations and Applications, the intersection of deep learning and genetics opens up new avenues for advancing our unders… Read more
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Description
Description
Deep Learning in Genetics and Genomics vol. 1, Foundations and Applications, the intersection of deep learning and genetics opens up new avenues for advancing our understanding of the genetic code, gene regulation, and the broader genomics landscape. The book not only covers the most up-to-date advancements in the field of deep learning in genetics and genomics, but also a wide spectrum of (sub) topics including medical and clinical genetics, predictive medicine, transcriptomic, and gene expression studies. In 21 chapters Deep Learning in Genetics and Genomics vol. 1, Foundations and Applications describes how AI and DL have become increasingly useful in genetics and genomics research where both play a crucial role by accelerating research, improving the understanding of the human genome, and enabling personalized healthcare. From the fundamentals concepts and practical applications of deep learning algorithms to a wide range of challenging problems from genetics and genomics, Deep Learning in Genetics and Genomics vol. 1, Foundations and Applications creates a better knowledge of the biological and genetics mechanisms behind disease illnesses and improves the forecasting abilities using the different methodologies described. This title offers a unique resource for wider, deeper, and in-depth coverage of recent advancement in deep learning-based approaches in genetics and genomics, helping researchers process and interpret vast amounts of genetic data, identify patterns, and make discoveries that would be challenging or impossible using traditional methods.
Key features
Key features
- Brings together fundamental concepts of genetics, genomics, and deep learning
- Includes how to build background of solution methodologies and design of mathematical and logical algorithms
- Delves into the intersection of deep learning and genetics, offering a comprehensive exploration of how deep learning techniques can be applied to various aspects of genomics
Readership
Readership
Researchers and students of biology, biostatistics, biomedical sciences, bioinformatics, health-informatics, and Interdisciplinary sciences
Table of contents
Table of contents
1. Basics of Genetics and Genomics
2. Introduction to Deep Learning
3. Decoding DNA: Deep Learning’s Impact on Genomic Exploration
4. Deep learning for Biological Data analysis
5. AI and Deep Learning in Cancer Genomics
6. Unravelling the Recent Developments in Applications and Challenges of AI in Cancer Biology: An overview
7. Unlocking the Potential of Deep Learning for Oncological Sequence Analysis: A Review
8. Deep Learning in Medical Genetics: A Review
9. Navigating the Genomic Landscape: A Deep Dive into Clinical Genetics with Deep Learning
10. Advancing Clinical Genomics: Bridging the Gap between Deep Learning Models and Interpretability for Improved Decision Support
11. Deep Learning in Clinical Genomics-based Diagnosis of Cancers
12. Predictive Precision: Unleashing Deep Learning in Comprehensive Medical Diagnosis and Treatment
13. Deep Learning in Predictive Medicine: Current State-of-the-art
14. Applications of AI in Cancer Genomics: A Way toward Intelligent Decision Systems in Healthcare
15. The Role of Deep Learning in Drug Discovery
16. Deep Learning in Drug Discovery: Revolutionizing the Path to New Medicines
17. Deep Learning Application in Genomics-based Toxicology Assessment
18. The Revolutionary Impact of Deep Learning in Transcriptomics and Gene Expression Analysis: A Genomic Paradigm Shift
19. Machine Learning Applications in Biological Network Analysis: Current State-of-the-Art
20. Data-driven Genomics: A Triad of Big Data, Cloud, and IoT in Genomics Research
21. Deep Learning in Variant Detection and Annotation
2. Introduction to Deep Learning
3. Decoding DNA: Deep Learning’s Impact on Genomic Exploration
4. Deep learning for Biological Data analysis
5. AI and Deep Learning in Cancer Genomics
6. Unravelling the Recent Developments in Applications and Challenges of AI in Cancer Biology: An overview
7. Unlocking the Potential of Deep Learning for Oncological Sequence Analysis: A Review
8. Deep Learning in Medical Genetics: A Review
9. Navigating the Genomic Landscape: A Deep Dive into Clinical Genetics with Deep Learning
10. Advancing Clinical Genomics: Bridging the Gap between Deep Learning Models and Interpretability for Improved Decision Support
11. Deep Learning in Clinical Genomics-based Diagnosis of Cancers
12. Predictive Precision: Unleashing Deep Learning in Comprehensive Medical Diagnosis and Treatment
13. Deep Learning in Predictive Medicine: Current State-of-the-art
14. Applications of AI in Cancer Genomics: A Way toward Intelligent Decision Systems in Healthcare
15. The Role of Deep Learning in Drug Discovery
16. Deep Learning in Drug Discovery: Revolutionizing the Path to New Medicines
17. Deep Learning Application in Genomics-based Toxicology Assessment
18. The Revolutionary Impact of Deep Learning in Transcriptomics and Gene Expression Analysis: A Genomic Paradigm Shift
19. Machine Learning Applications in Biological Network Analysis: Current State-of-the-Art
20. Data-driven Genomics: A Triad of Big Data, Cloud, and IoT in Genomics Research
21. Deep Learning in Variant Detection and Annotation
Product details
Product details
- Edition: 1
- Latest edition
- Published: November 28, 2024
- Language: English
About the editor
About the editor
KR
Khalid Raza
Dr. Khalid Raza is an Associate Professor at the Department of Computer Science, Jamia Millia Islamia, New Delhi, India, and an Adjunct Professor at UCSI University, Malaysia. He has over 14 years of teaching and research experience and previously served as an ICCR Chair Visiting Professor at Ain Shams University, Egypt. Dr. Raza has published more than 160 peer-reviewed papers and authored/edited over 15 books with Springer, Elsevier, and CRC Press. He serves as Academic Editor of PLoS ONE, BMC Artificial Intelligence, and Guest Editor of npj Precision Oncology, JoVE, and several other journals. Recipient of Clarivate’s (Web of Science) India Excellence Research Citation Award 2025, Dr. Raza is consistently featured in the World’s Top 2% Scientists list (2022–2025). His research focuses on AI, bioinformatics, and health informatics
Affiliations and expertise
Department of Computer Science, Jamia Millia Islamia (Central University), Jamia Nagar, New Delhi, IndiaView book on ScienceDirect
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