Deep Learning in Genetics and Genomics

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

• 1. Basics of Genetics and Genomics2. Introduction to Deep Learning3. Decoding DNA: Deep Learning’s Impact on Genomic Exploration4. Deep learning for Biological Data analysis5. AI and Deep Learning in Cancer Genomics6. Unravelling the Recent Developments in Applications and Challenges of AI in Cancer Biology: An overview7. Unlocking the Potential of Deep Learning for Oncological Sequence Analysis: A Review8. Deep Learning in Medical Genetics: A Review9. Navigating the Genomic Landscape: A Deep Dive into Clinical Genetics with Deep Learning10. Advancing Clinical Genomics: Bridging the Gap between Deep Learning Models and Interpretability for Improved Decision Support11. Deep Learning in Clinical Genomics-based Diagnosis of Cancers12. Predictive Precision: Unleashing Deep Learning in Comprehensive Medical Diagnosis and Treatment13. Deep Learning in Predictive Medicine: Current State-of-the-art14. Applications of AI in Cancer Genomics: A Way toward Intelligent Decision Systems in Healthcare15. The Role of Deep Learning in Drug Discovery16. Deep Learning in Drug Discovery: Revolutionizing the Path to New Medicines17. Deep Learning Application in Genomics-based Toxicology Assessment18. The Revolutionary Impact of Deep Learning in Transcriptomics and Gene Expression Analysis: A Genomic Paradigm Shift19. Machine Learning Applications in Biological Network Analysis: Current State-of-the-Art20. Data-driven Genomics: A Triad of Big Data, Cloud, and IoT in Genomics Research21. Deep Learning in Variant Detection and Annotation