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计算和统计表观基因组学-Computational and Statistical Epigenomics

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标题(title):Computational and Statistical Epigenomics
计算和统计表观基因组学
作者(author):Andrew E. Teschendorff (eds.)
出版社(publisher):Springer Netherlands
大小(size):5 MB (5149273 bytes)
格式(extension):pdf
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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.



Table of contents :
Front Matter....Pages i-v
Front Matter....Pages 1-1
Introduction to Data Types in Epigenomics....Pages 3-34
DNA Methylation and Cell-Type Distribution....Pages 35-50
A General Strategy for Inter-sample Variability Assessment and Normalisation....Pages 51-68
Quantitative Comparison of ChIP-Seq Data Sets Using MAnorm....Pages 69-90
Model-Based Clustering of DNA Methylation Array Data....Pages 91-123
Front Matter....Pages 125-125
Integrative Epigenomics....Pages 127-139
Towards a Mechanistic Understanding of Epigenetic Dynamics....Pages 141-160
Systems Epigenomics and Applications to Ageing and Cancer....Pages 161-185
Epigenomic Biomarkers for the Advance of Personalized Medicine....Pages 187-217

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