Artificial Intelligence in Genomics

Introduction.- Genomics in the Age of Artificial Intelligence.- Data Foundations: Sequencing, Multi-Omics, and Data Quality.- Classical Machine Learning Methods in Genomics.- Deep Learning Architectures for Genomic Sequences and Structures.- Graph Neural Networks and Biological Networks.- Self-Supervised and Foundation Models in Genomic Research.- Integrative Multi-Omics Modeling and Data Fusion.- Interpretability, Explainability, and Causality in Genomic AI.- Federated Learning and Privacy-Preserving Genomics.- AI for Clinical Genomics: Diagnostics and Prognostics.- AI-Driven Drug Discovery and Pharmacogenomics.- Population Genomics and Public Health Applications.- Ethical, Legal, and Societal Implications in Genomic AI.- Future Perspectives: Generative Models, Digital Twins, and Personalized Medicine.- Conclusion.

• Erscheinungsdatum: 06.05.2026
• Autor/Autorin: Khalid Shaikh,Rohit Thanki,Sejal Shah
• Reihe: Synthesis Collection of Technology (R0)
• Format: E-Book
• Dateiformat: PDF
• Kopierschutz: Wasserzeichen
• Dateigröße: 7.5 MB
• Verlag: SPRINGER
• Sprache: Englisch
• Umfang: 187 Seiten
• ISBN: 9783032254863
• Lieferung: Sofort per Download
• Hinweis: Sofort per Download lieferbar. Kein physischer Versand.
• Kompatibilität: Lesbar auf Geräten und Apps mit PDF-Unterstützung.