Methodologies of Multi-Omics Data Integration and Data Mining: Techniques and Applications

This book discusses data integration and data mining methods for multi-omics research, focusing on cancer, inflammation, and microbiome studies. It bridges the gap between biomedical multi-omics big data and data-mining techniques and provides insights for researchers and practitioners.

Format: Hardback
Length: 167 pages
Publication date: 16 January 2023
Publisher: Springer Verlag, Singapore

In the era of omics, the sheer volume of multi-omics data from diverse sources presents a formidable challenge, but it also holds immense potential for various biomedical and clinical applications. This comprehensive book delves into the realm of data integration and data mining techniques specifically tailored for multi-omics research. It offers a detailed and illustrative explanation, accompanied by supportive examples, to elucidate the "what," "why," and "how" of this interdisciplinary field. The book is structured into eight chapters, with one dedicated to an introduction, four chapters focusing on omics integration techniques, utilizing various omics data resources and data-mining methods, and three chapters showcasing applications of multi-omics analyses through diverse data mining approaches.

The objective of this book is to bridge the gap between biomedical multi-omics big data and the data-mining techniques necessary for optimal bioinformatics practices and profound insights into biomedical questions. It appeals to researchers and practitioners interested in conducting multi-omics studies in cancer, inflammation diseases, and microbiome research. By unraveling the complexities of multi-omics data, this book empowers scholars and practitioners to unravel the underlying mechanisms, identify biomarkers, and develop personalized treatments for a wide range of diseases.

Weight: 442g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811982095
Edition number: 1st ed. 2023