Application Of Novel Statistical And Machine Learning Methods To High Dimensional Clinical Cancer And Multi Omics Data

Application of Novel Statistical and Machine-learning Methods to High-dimensional Clinical Cancer and (Multi-)Omics data

Artificial Intelligence Bioinformatics: Development and Application of Tools for Omics and Inter-Omics Studies

Applications of Multi-Omics

In the era of big data and personalized medicine, Applications of Multi-Omics serves as a comprehensive guide to integrating biological data across genomics, transcriptomics, proteomics, metabolomics, and epigenomics. This book explores how multi-omics technologies provide a holistic view of biological systems, transforming our understanding of human health, disease mechanisms, drug development, and environmental science. Written for researchers, healthcare professionals, and students in life sciences, this book breaks down complex concepts into accessible insights, covering key methodologies, computational approaches, and real-world applications. From precision medicine and biomarker discovery to AI-driven data integration and ethical considerations, Applications of Multi-Omics provides a deep dive into how multi-layered biological data is revolutionizing biomedical research and healthcare. Whether you are an academic researcher seeking to integrate multi-omics in your studies, a clinician exploring omics-driven diagnostics, or a data scientist working at the intersection of AI and life sciences, this book is an essential resource. It highlights emerging trends, challenges, and future directions in multi-omics, paving the way for groundbreaking discoveries in personalized medicine, biotechnology, and agricultural research. Join the multi-omics revolution and uncover the intricate biological networks shaping the future of science and medicine.