Editors:
- Introduces computational and statistical tools needed for a successful translation from bench to bedside
- A special focus on DNA methylation data
- Covers the application of these tools
- Includes supplementary material: sn.pub/extras
Part of the book series: Translational Bioinformatics (TRBIO, volume 7)
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (9 chapters)
-
Front Matter
-
Normalization and Analysis Methods for DNA Methylation and ChIP-Seq Data
-
Front Matter
-
-
Integrative and Medical Epigenomics
-
Front Matter
-
About this book
This book introduces the reader to modern computational and statistical tools for translational epigenomics research. Over the last decade, epigenomics has emerged as a key area of molecular biology, epidemiology and genome medicine. Epigenomics not only offers us a deeper understanding of fundamental cellular biology, but also provides us with the basis for an improved understanding and management of complex diseases. From novel biomarkers for risk prediction, early detection, diagnosis and prognosis of common diseases, to novel therapeutic strategies, epigenomics is set to play a key role in the personalized medicine of the future. In this book we introduce the reader to some of the most important computational and statistical methods for analyzing epigenomic data, with a special focus on DNA methylation. Topics include normalization, correction for cellular heterogeneity, batch effects, clustering, supervised analysis and integrative methods for systems epigenomics. This book will be of interest to students and researchers in bioinformatics, biostatistics, biologists and clinicians alike.
Dr. Andrew E. Teschendorff is Head of the Computational Systems Genomics Lab at the CAS-MPG Partner Institute for Computational Biology, Shanghai, China, as well as an Honorary Research Fellow at the UCL Cancer Institute, University College London, UK.
Reviews
“This volume in the Translational Bioinformatics series introduces modern computational and statistical tools for translational epigenomic research with a special focus on DNA methylation. … This is a valuable resource for students, clinicians, and researchers who wish to understand the basics of modern computational and statistical tools for translational epigenomics research. The analytical, storage-related, and interpretive methods discussed in this book hold great promise in helping improve prediction, early diagnosis, severity monitoring, therapeutic effect, and prognosis of human diseases.” (Pooja Sethi, Doody’s Book Reviews, July, 2015)
Editors and Affiliations
-
CAS Key Laboratory of Computational Biology, Chinese Academy of Sciences and Max-Planck Gesellschaft Partner, Institute for Computational Biology, Shanghai, China
Andrew E. Teschendorff
Bibliographic Information
Book Title: Computational and Statistical Epigenomics
Editors: Andrew E. Teschendorff
Series Title: Translational Bioinformatics
DOI: https://doi.org/10.1007/978-94-017-9927-0
Publisher: Springer Dordrecht
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: Springer Science+Business Media Dordrecht 2015
Hardcover ISBN: 978-94-017-9926-3Published: 29 May 2015
Softcover ISBN: 978-94-024-0343-5Published: 23 October 2016
eBook ISBN: 978-94-017-9927-0Published: 12 May 2015
Series ISSN: 2213-2775
Series E-ISSN: 2213-2783
Edition Number: 1
Number of Pages: V, 217
Number of Illustrations: 1 b/w illustrations, 41 illustrations in colour
Topics: Bioinformatics, Computer Appl. in Life Sciences, Molecular Medicine, Epidemiology