Deep Learning in Genetics and Genomics
Volume 2: Advanced Applications
- 1st Edition - November 28, 2024
- Latest edition
- Editor: Khalid Raza
- Language: English
Deep Learning in Genetics and Genomics: Vol. 2 (Advanced Applications) delves into the Deep Learning methods and their applications in various fields of studies, including geneti… Read more
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Description
Description
Deep Learning in Genetics and Genomics: Vol. 2 (Advanced Applications) delves into the Deep Learning methods and their applications in various fields of studies, including genetics and genomics, bioinformatics, health informatics and medical informatics generating the momentum of today's developments in the field. In 25 chapters this title covers advanced applications in the field which includes deep learning in predictive medicines), analysis of genetic and clinical features, transcriptomics and gene expression patterns analysis, clinical decision support in genetic diagnostics, deep learning in personalised genomics and gene editing, and understanding genetic discoveries through Explainable AI. Further, it also covers various deep learning-based case studies, making this book a unique resource for wider, deeper, and in-depth coverage of recent advancement in deep learning based approaches. This volume is not only a valuable resource for health educators, clinicians, and healthcare professionals but also to graduate students of genetics, genomics, biology, biostatistics, biomedical sciences, bioinformatics, and interdisciplinary sciences.
Key features
Key features
- Embraces the potential that deep learning holds for understanding genome biology
- Encourages further advances in this area, extending to all aspects of genomics research
- Provides Deep Learning algorithms in genetic and genomic research
Readership
Readership
Researchers and students of biology, biostatistics, biomedical sciences, bioinformatics, health informatics, and Interdisciplinary sciences
Table of contents
Table of contents
1. Enhancing Predictive Accuracy in Diabetic Retinopathy: Deep Learning Algorithms in Predictive Medicine
2. Deep Learning in Predictive Medicine Exemplified by AI-Mediated Flu Surveillance in USA
3. Towards Equitable Precision Medicine: Investigating the Transferability of Deep Learning Models in Clinical Genetics across Diverse Populations
4. Analysis of Genetic and Clinical Features in Neuro Disorders Using Deep Learning Models
5. Deep Learning Insights into Transcriptomics and Gene Expression Patterns analysis
6. Role of AI and Deep Learning in Clinical Cancer Genomics Allowing Targeted Therapies for Oncology
7. Deep Learning Approaches for Interpreting Non-coding Regions in Ovarian Cancer
8. Advancements in AI-driven Spatial Transcriptomics: Decoding Cellular Complexity
9. Neural Architectures for Genomic Understanding: Deep Dive into Epigenome and Chromatin Structure 10. Deep Learning in Personalized Genomics and Gene Editing
11. Deep Learning-based Model for Prediction of Prognostic Genes of Breast Cancer using Transcriptomic data
12. Deciphering the Complexity of Life: Advances in Genomic Image Analysis
13. Qualitative Study on Steganography of Genomic Image Data for Secure Data Transmission Using Deep Learning Models
14. Generative AI in Genetics: A Comprehensive Review
15. Integrating Computational Biology and Multi-Omics Data for Precision Medicine in Personalized Cancer Treatment
16. Deep Generative Models in Utilitarian and Metamorphic Genomics - Intellectual Benefits
17. Transfer Learning in High-Dimensional Genomic Data Analysis
18. Inequality in Genetic Healthcare: Bridging Gaps with Deep Learning Innovations in LMICs
19. Harmonizing Health Horizons: Bridging Research Gaps in Big Data Management for Transformative Clinical Insights
20. Bridging the Gap: Understanding Genetic Discoveries through Explainable AI
21. Explainable AI in Genetics: A Case Study
22. Deep Learning in Predicting Genetic Disorders: A Case Study
23. AI and Deep Learning in Single-Cell Omics Data Analysis: A Case Study
24. Deep Learning for Network Building and Network Analysis of Biological networks: A Case Study
25. Transformer Networks and Autoencoders in Genomics and Genetic Data Interpretation: A Case Study
2. Deep Learning in Predictive Medicine Exemplified by AI-Mediated Flu Surveillance in USA
3. Towards Equitable Precision Medicine: Investigating the Transferability of Deep Learning Models in Clinical Genetics across Diverse Populations
4. Analysis of Genetic and Clinical Features in Neuro Disorders Using Deep Learning Models
5. Deep Learning Insights into Transcriptomics and Gene Expression Patterns analysis
6. Role of AI and Deep Learning in Clinical Cancer Genomics Allowing Targeted Therapies for Oncology
7. Deep Learning Approaches for Interpreting Non-coding Regions in Ovarian Cancer
8. Advancements in AI-driven Spatial Transcriptomics: Decoding Cellular Complexity
9. Neural Architectures for Genomic Understanding: Deep Dive into Epigenome and Chromatin Structure 10. Deep Learning in Personalized Genomics and Gene Editing
11. Deep Learning-based Model for Prediction of Prognostic Genes of Breast Cancer using Transcriptomic data
12. Deciphering the Complexity of Life: Advances in Genomic Image Analysis
13. Qualitative Study on Steganography of Genomic Image Data for Secure Data Transmission Using Deep Learning Models
14. Generative AI in Genetics: A Comprehensive Review
15. Integrating Computational Biology and Multi-Omics Data for Precision Medicine in Personalized Cancer Treatment
16. Deep Generative Models in Utilitarian and Metamorphic Genomics - Intellectual Benefits
17. Transfer Learning in High-Dimensional Genomic Data Analysis
18. Inequality in Genetic Healthcare: Bridging Gaps with Deep Learning Innovations in LMICs
19. Harmonizing Health Horizons: Bridging Research Gaps in Big Data Management for Transformative Clinical Insights
20. Bridging the Gap: Understanding Genetic Discoveries through Explainable AI
21. Explainable AI in Genetics: A Case Study
22. Deep Learning in Predicting Genetic Disorders: A Case Study
23. AI and Deep Learning in Single-Cell Omics Data Analysis: A Case Study
24. Deep Learning for Network Building and Network Analysis of Biological networks: A Case Study
25. Transformer Networks and Autoencoders in Genomics and Genetic Data Interpretation: A Case Study
Product details
Product details
- Edition: 1
- Latest edition
- Published: December 5, 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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