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.
- 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
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ISBN-13
978-0-443-27524-1 (9780443275241)
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1. Enhancing Predictive Accuracy in Diabetic Retinopathy: Deep Learning Algorithms in Predictive Medicine2. Deep Learning in Predictive Medicine Exemplified by AI-Mediated Flu Surveillance in USA3. Towards Equitable Precision Medicine: Investigating the Transferability of Deep Learning Models in Clinical Genetics across Diverse Populations4. Analysis of Genetic and Clinical Features in Neuro Disorders Using Deep Learning Models5. Deep Learning Insights into Transcriptomics and Gene Expression Patterns analysis6. Role of AI and Deep Learning in Clinical Cancer Genomics Allowing Targeted Therapies for Oncology7. Deep Learning Approaches for Interpreting Non-coding Regions in Ovarian Cancer8. Advancements in AI-driven Spatial Transcriptomics: Decoding Cellular Complexity9. Neural Architectures for Genomic Understanding: Deep Dive into Epigenome and Chromatin Structure 10. Deep Learning in Personalized Genomics and Gene Editing11. Deep Learning-based Model for Prediction of Prognostic Genes of Breast Cancer using Transcriptomic data12. Deciphering the Complexity of Life: Advances in Genomic Image Analysis13. Qualitative Study on Steganography of Genomic Image Data for Secure Data Transmission Using Deep Learning Models14. Generative AI in Genetics: A Comprehensive Review15. Integrating Computational Biology and Multi-Omics Data for Precision Medicine in Personalized Cancer Treatment16. Deep Generative Models in Utilitarian and Metamorphic Genomics - Intellectual Benefits17. Transfer Learning in High-Dimensional Genomic Data Analysis18. Inequality in Genetic Healthcare: Bridging Gaps with Deep Learning Innovations in LMICs19. Harmonizing Health Horizons: Bridging Research Gaps in Big Data Management for Transformative Clinical Insights20. Bridging the Gap: Understanding Genetic Discoveries through Explainable AI21. Explainable AI in Genetics: A Case Study22. Deep Learning in Predicting Genetic Disorders: A Case Study23. AI and Deep Learning in Single-Cell Omics Data Analysis: A Case Study24. Deep Learning for Network Building and Network Analysis of Biological networks: A Case Study25. Transformer Networks and Autoencoders in Genomics and Genetic Data Interpretation: A Case Study
