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Home > Biology, life sciences > Life sciences: general issues > Computational biology / bioinformatics > Deep Learning in Genetics and Genomics: Volume 2: Advanced Applications
Deep Learning in Genetics and Genomics: Volume 2: Advanced Applications

Deep Learning in Genetics and Genomics: Volume 2: Advanced Applications


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Deep Learning in Genetics and Genomics, vol. 2: Advanced Applications

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

About the Author :
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


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Product Details
  • ISBN-13: 9780443275234
  • Publisher: Elsevier Science Publishing Co Inc
  • Publisher Imprint: Academic Press Inc
  • Height: 235 mm
  • No of Pages: 468
  • Weight: 970 gr
  • ISBN-10: 0443275238
  • Publisher Date: 05 Dec 2024
  • Binding: Paperback
  • Language: English
  • Sub Title: Volume 2: Advanced Applications
  • Width: 191 mm


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