Elsevier Personalized Cancer Medicine through Multiomics

Personalized Cancer Medicine through Multiomics explores the integration of multiomics to transform cancer diagnosis and treatment. The book delves into how the convergence of genomics, transcriptomics, proteomics, and metabolomics offers a comprehensive understanding of cancer biology, surpassing traditional single-omics approaches. Sections detail advancements in high-throughput technologies and computational methods, including machine learning, that enable the analysis of complex cancer datasets. Additional content discusses how multiomics identifies unique molecular signatures, novel therapeutic targets, and biomarkers, facilitating precise and individualized treatment strategies, particularly for a heterogeneous cancers. For academics, this book serves as an essential resource, compiling fragmented research into a single, coherent volume. It provides foundational knowledge, the latest advancements, and practical applications of multiomics in personalized medicine. Researchers will benefit from interdisciplinary approaches, real-world examples, and cutting-edge methodologies, making it an invaluable reference for advancing their work in oncology. Comprehensive coverage of genomics, transcriptomics, proteomics, metabolomics, and other omics to provide a holistic view of cancer mechanisms. Detailed insights into high-throughput platforms, machine learning methods, and AI-driven analytics for complex cancer datasets. Real-world case studies demonstrating successful applications of multiomics in achieving personalised cancer care.