Artificial Intelligence in Molecular Biology and Medicine

Artificial Intelligence in Molecular Biology and Medicine: Advanced Applications in Biomedical Research and Precision Medicine, Volume 2 is part of the Artificial Intelligence in the Life Sciences Series, a comprehensive series exploring how artificial intelligence is transforming the biological, biomedical, and health sciences.Building on the foundations established in Volume 1, this volume takes readers deeper into the advanced and practical applications of artificial intelligence, machine learning, deep learning, bioinformatics, and computational biology in molecular research and modern medicine. It examines how intelligent computational methods are being applied to epigenetics, multi-omics integration, protein structure prediction, synthetic biology, genome engineering, precision medicine, disease diagnosis, medical imaging, oncology, and clinical decision support.Readers will explore key topics including:AI in epigenetics and gene regulationMulti-omics integration across genomics, transcriptomics, proteomics, and metabolomicsAI-powered bioinformatics and biological data analysisProtein folding and structural biology, including AlphaFold and RoseTTAFoldSynthetic biology, genome engineering, and CRISPR designPrecision medicine, biomarker discovery, patient stratification, risk prediction, and personalized therapeuticsAI-assisted disease diagnosis and early detectionMedical imaging, radiomics, radiology, and digital pathologyCancer genomics, precision oncology, treatment-response prediction, and prognosisClinical decision support, electronic health record intelligence, predictive healthcare, ICU monitoring, remote patient monitoring, and future intelligent hospitalsWritten in a clear and accessible academic style, the book connects artificial intelligence with molecular biology, biomedical research, and medicine while emphasizing the biological and clinical interpretation of computational results. It also examines critical challenges including data quality, model validation, generalizability, privacy, bias, biosafety, and the responsible implementation of AI in biomedical and clinical environments.Designed for students, researchers, lecturers, healthcare professionals, bioinformaticians, data scientists, biotechnology professionals, and lifelong learners, Volume 2 provides a comprehensive guide to the rapidly evolving intersection of artificial intelligence, life sciences, biomedical research, and precision healthcare.As a volume in the Artificial Intelligence in the Life Sciences Series, this book contributes to a broader learning pathway for readers seeking to understand how AI is reshaping biological discovery and healthcare. Whether your interest is in analyzing complex biological data, predicting protein structures, improving genome engineering, discovering biomarkers, personalizing treatments, interpreting medical images, or supporting clinical decisions, this volume provides the concepts and applications needed to understand the next generation of AI-enabled biomedical research and medicine.