AI and Big Data Sciences for Bioinformatics and Systems Medicine
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This book aims to provide a comprehensive overview of how artificial intelligence (AI) and big data analytics are transforming bioinformatics and biomedical research. It covers a wide range of computational methods applied to biomedical big data, including genomics, transcriptomics, proteomics, and imaging data, with a focus on their role in precision medicine. The book is structured to guide readers from foundational AI models and data integration techniques to advanced applications in systems biology and drug discovery. It explores key topics such as single-cell and spatial omics analysis, g...
This book aims to provide a comprehensive overview of how artificial intelligence (AI) and big data analytics are transforming bioinformatics and biomedical research. It covers a wide range of computational methods applied to biomedical big data, including genomics, transcriptomics, proteomics, and imaging data, with a focus on their role in precision medicine. The book is structured to guide readers from foundational AI models and data integration techniques to advanced applications in systems biology and drug discovery. It explores key topics such as single-cell and spatial omics analysis, genetic variation studies, and computational modeling of disease processes. Additionally, it highlights cutting-edge approaches in synthetic biology, mRNA optimization, and small molecule generation. Designed for researchers, bioinformaticians, and clinicians, this book bridges the gap between computational sciences and biomedical applications. It aims to equip readers with the necessary knowledge to develop AI-driven solutions for diagnosing diseases, predicting treatment responses, and designing novel therapeutics. By integrating theoretical insights with real-world applications, the book serves as both an educational resource and a reference for ongoing advancements in AI-driven biomedical research.