Artificial Intelligence in Genomics
Description
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.
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Khalid Shaikh is the founder and CEO of Prognica Labs, a healthtech company. Prognica Labs is focused on revolutionizing the healthcare sector through artificial intelligence and advanced analytics, particularly in the early detection of diseases. His work is centered around leveraging technology to improve patient outcomes, reduce healthcare costs, and make advanced diagnostic tools more accessible to a broader population. Khalid Shaikh is serial entrepreneur, researcher, author, and business strategist. He is also a member of HBR Advisory Council and has received numerous awards for his innovations and contribution in healthcare and public health. In addition to his professional commitments, he also gives back to the aspiring entrepreneur community by serving as an advisor and mentor. He has published and lectured extensively on healthcare performance improvement, digitalization, and innovation.
Dr. Rohit Thanki is an expert in Artificial Intelligence, Medical Informatics, and Digital Health with experience in enterprise AI and Healthcare AI in India, the Middle East, and Germany. Previously, he served in a senior leadership role at KRiAN GmbH, where he developed CE-certified Software as a Medical Device (SaMD) for medical diagnostics and rehabilitation. He was also Head of Research & Development at Prognica Labs in Dubai, focusing on AI-driven breast cancer screening solutions. He holds a Ph.D. in Electronics and Communication Engineering from C. U. Shah University, India, with research on privacy-preserving multibiometric systems. He also has bachelor's and master's degrees in Electronics and Communication Engineering. His research interests include explainable AI for healthcare, medical imaging, biomedical signal processing, multimodal and generative AI systems, and regulatory-compliant clinical AI agents. He has contributed to the development of AI systems covering X-ray, CT, MRI, ultrasound, mammography, histopathology, and physiological data analysis. He has taught courses in image processing, signal processing, communication systems, navigational and radar communication, satellite communication, and VLSI as an Assistant Professor and Visiting Lecturer in India. He serves on Ph.D. examination boards and supervises postgraduate research in both India and Germany. He has published over 110 Scopus-indexed articles and 20 scholarly books, with more than 1,800 citations and a strong h-index. He is a Senior Member of IEEE, an editorial board member for BMC Digital Health and PLOS One, and an active peer reviewer for leading journals.
Dr. Sejal Shah is working as an Associate Professor and Head at Department of Bioinformatics, Marwadi University. She has been selected in top 10 women scientists and awarded Indo-US women in STEMM fellowship (2019) by DST, Government of India and IUSSTF jointly to pursue post-doctoral research at USA and she joined Ohio State University for research in pediatric leukemia. She has been selected among 15 women scientists all over India by DST, KIRAN division for cancer research training organized at Mysore University, Mysore in 2018. She has been also awarded "Woman Scientist Fellow" in May 2012, in Women Scientist Scheme-A (DST/ WOS-A) of Department of Science and Technology, New Delhi, Government of India. Recently during October 2024, Dr. Shah was invited as an expert speaker and program coordinator for the Reverse Vaccinology workshop by IEEE HTC 25 at Chiba University, Tokyo, JAPAN and IEEE HTC 24 at Kuala Lumpur, Malaysia during October 2024. Moreover, she has served as an Erasmus plus Faculty at University of Pitesti, Romania as well, as a part of Erasmus plus Faculty mobility Program funded by European union during October 2023. She has 14 years of experience in the field of Cancer omics research, Artificial Intelligence, Machine learning, Biotechnology, Bioinformatics and Nanotechnology. During this period, she has been actively involved in the teaching and cancer research. Dr. Shah also extending her duty as a Cancer Geneticist and molecular tumor board member at several Cancer hospitals in Gujarat specially for hereditary cancers. She and her team currently working on oral cancer, cervical cancer and breast cancer. She is an advisor of IEEE EMBS (Engineering in Medicine and Biology) student branch chapter, Marwadi University, Gujarat section. She is IEEE WIE (Women in Engineering) member of Gujarat Section. She is associate member of American Association of Cancer Research (AACR) and scientific decoder at COVID 19 Omics Research Consortium (CORC). She has more than 67 publications, 2 authored books on oral cancer and cervical cancer by Springer Nature, 9 patents and number of research projects completed to her credit from various funding agencies.
Content
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.