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Main Title Computational and Statistical Epigenomics [electronic resource] /
Type EBOOK
Other Authors
Author Title of a Work
Teschendorff, Andrew E.
Publisher Springer Netherlands : Imprint: Springer,
Year Published 2015
Call Number QH324.2-324.25
ISBN 9789401799270
Subjects Life sciences ; Medicine ; Epidemiology ; Bioinformatics ; Biology--Data processing
Internet Access
Description Access URL
http://dx.doi.org/10.1007/978-94-017-9927-0
Collation V, 217 p. 42 illus., 41 illus. in color. online resource.
Notes Due to license restrictions, this resource is available to EPA employees and authorized contractors only
Contents Notes 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.
Place Published Dordrecht
Corporate Au Added Ent SpringerLink (Online service)
Title Ser Add Ent Translational Bioinformatics, 7
Host Item Entry Springer eBooks
PUB Date Free Form 2015
Series Title Untraced Translational Bioinformatics, 7
BIB Level m
Medium computer
Content text
Carrier online resource
Cataloging Source OCLC/T
OCLC Time Stamp 20150519174153
Language eng
Origin SPRINGER
Type EBOOK
OCLC Rec Leader 03027nam a22004935i 45