Artificial Intelligence in Genomics
Methods, Applications, and Clinical Translation
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Beschreibung
This book provides a comprehensive and accessible exploration of how Artificial Intelligence (AI) is transforming the field of Genomics and personalized medicine. The book brings together the latest methods, tools, and real-world applications that enable scientists and clinicians to interpret complex genetic data, discover disease-causing patterns, and design precision therapies. Covering topics from deep learning and multi-omics integration to ethical and regulatory considerations, the book bridges the gap between computational innovation and clinical translation. Designed for researchers, students, healthcare professionals, and biotech innovators, this book offers clear explanations, illustrative case studies, and forward-looking insights into how AI is shaping the future of medicine and human health.
- Presents AI applications in genomic science, from foundational methods to advanced clinical and translational use cases;
- Connects academic AI research with practical implementation in healthcare, biotechnology, and personalized medicine;
- Written for computational and life science audiences, integrating biology, data science, and clinical perspectives.
This book provides a comprehensive and accessible exploration of how Artificial Intelligence (AI) is transforming the field of Genomics and personalized medicine. The book brings together the latest methods, tools, and real-world applications that enable scientists and clinicians to interpret complex genetic data, discover disease-causing patterns, and design precision therapies. Covering topics from deep learning and multi-omics integration to ethical and regulatory considerations, the book bridges the gap between computational innovation and clinical translation. Designed for researchers, students, healthcare professionals, and biotech innovators, this book offers clear explanations, illustrative case studies, and forward-looking insights into how AI is shaping the future of medicine and human health.
Presents AI applications in genomic science, from foundational methods to advanced clinical and translational use cases Connects academic AI research with practical implementation in healthcare, biotechnology, and personalized medicine Written for computational and life science audiences, integrating biology, data science, and clinical perspectives
Autor*in
Khalid Shaikh
Themen in »Artificial Intelligence in Genomics«
Genomics in Artificial Intelligence Data Foundations Sequencing, Multi-Omics, and Data Quality Machine Learning Methods in Genomics Deep Learning Architectures Graph Neural Networks and Biological Networks Self-Supervised and Foundation Models