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Title
Methodologies of multi-omics data integration and data mining : techniques and applications / Kang Ning, editor.
ISBN
9789811982101 (electronic bk.)
9811982104 (electronic bk.)
9789811982095
9811982090
Published
Singapore : Springer, [2023]
Copyright
©2023
Language
English
Description
1 online resource (xi, 167 pages) : illustrations.
Item Number
10.1007/978-981-19-8210-1 doi
Call Number
QA76.9.D338
Dewey Decimal Classification
005.7/3
Summary
This book features multi-omics big-data integration and data-mining techniques. In the omics age, paramount of multi-omics data from various sources is the new challenge we are facing, but it also provides clues for several biomedical or clinical applications. This book focuses on data integration and data mining methods for multi-omics research, which explains in detail and with supportive examples the "What", "Why" and "How" of the topic. The contents are organized into eight chapters, out of which one is for the introduction, followed by four chapters dedicated for omics integration techniques focusing on several omics data resources and data-mining methods, and three chapters dedicated for applications of multi-omics analyses with application being demonstrated by several data mining methods. This book is an attempt to bridge the gap between the biomedical multi-omics big data and the data-mining techniques for the best practice of contemporary bioinformatics and the in-depth insights for the biomedical questions. It would be of interests for the researchers and practitioners who want to conduct the multi-omics studies in cancer, inflammation disease, and microbiome researches.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Digital File Characteristics
text file PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed January 23, 2023).
Series
Translational bioinformatics ; v. 19. 2213-2783
Available in Other Form
Printed edition 9789811982095
Printed edition 9789811982118
Printed edition 9789811982125
Chapter 1. Introduction to multi-omics
Part 1. Omics integration techniques
Chapter 2. Biomedical applications: the need for multi-omics
Chapter 3. Omics technologies and big data
Chapter 4. Multi-omics data mining techniques: algorithms and software
Part 2. Applications of multi-omics analyses
Chapter 5. Multi-omics data analysis for cancer research: colorectal cancer, liver cancer and lung cancer
Chapter 6. Multi-omics data analysis for inflammation disease research: correlation analysis, causal analysis and network analysis
Chapter 7. Microbiome data analysis and interpretation: correlation inferences and dynamic pattern discovery
Chapter 8. Current progress of bioinformatics for human health.
