Artificial intelligence in genomics methods, applications, and clinical translation Khalid Shaikh, Rohit Thanki, Sejal Shah

Format:

Book

Author/Creator:

Shaikh, Khalid (Of Prognica Labs), author.

Thanki, Rohit M., author.

Śāha, Sejala, author.

Series:

Synthesis lectures on engineering, science, and technology 2690-0327

Language:

English

Subjects (All):

Genomics--Data processing.

Genomics.

Artificial intelligence--Medical applications.

Artificial intelligence.

Physical Description:

1 online resource

Place of Publication:

Cham Springer [2026]

Summary:

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.

Contents:

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

Notes:

Includes bibliographical references and index

Online resource; title from PDF title page (SpringerLink, viewed May 22, 2026)

Other Format:

Print version Shaikh, Khalid Artificial Intelligence in Genomics

ISBN:

9783032254863

3032254868

OCLC:

1592447105

Access Restriction:

Restricted for use by site license