000727104 000__ 02774cam\a2200397Ii\4500 000727104 001__ 727104 000727104 005__ 20230306140800.0 000727104 006__ m\\\\\o\\d\\\\\\\\ 000727104 007__ cr\cn\nnnunnun 000727104 008__ 150514s2015\\\\ne\\\\\\ob\\\\000\0\eng\d 000727104 020__ $$a9789401799270$$qelectronic book 000727104 020__ $$a940179927X$$qelectronic book 000727104 020__ $$z9789401799263 000727104 035__ $$aSP(OCoLC)ocn908931801 000727104 035__ $$aSP(OCoLC)908931801 000727104 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dN$T$$dGW5XE$$dYDXCP$$dIDEBK$$dE7B$$dNUI$$dEBLCP$$dCDX 000727104 049__ $$aISEA 000727104 050_4 $$aRB155 000727104 08204 $$a616.042$$223 000727104 24500 $$aComputational and statistical epigenomics$$h[electronic resource] /$$cAndrew E. Teschendorff, editor. 000727104 264_1 $$aDordrecht [Netherlands] :$$bSpringer,$$c[2015] 000727104 300__ $$a1 online resource. 000727104 336__ $$atext$$btxt$$2rdacontent 000727104 337__ $$acomputer$$bc$$2rdamedia 000727104 338__ $$aonline resource$$bcr$$2rdacarrier 000727104 4901_ $$aTranslational bioinformatics ;$$vVolume 7 000727104 504__ $$aIncludes bibliographical references. 000727104 506__ $$aAccess limited to authorized users. 000727104 520__ $$aThis book introduces the reader to modern computational and statistical tools for translational epigenomics research. Over the last decade, epigenomics has emerged as a key area of molecular biology, epidemiology and genome medicine. Epigenomics not only offers us a deeper understanding of fundamental cellular biology, but also provides us with the basis for an improved understanding and management of complex diseases. From novel biomarkers for risk prediction, early detection, diagnosis and prognosis of common diseases, to novel therapeutic strategies, epigenomics is set to play a key role in the personalized medicine of the future. In this book we introduce the reader to some of the most important computational and statistical methods for analyzing epigenomic data, with a special focus on DNA methylation. Topics include normalization, correction for cellular heterogeneity, batch effects, clustering, supervised analysis and integrative methods for systems epigenomics. This book will be of interest to students and researchers in bioinformatics, biostatistics, biologists and clinicians alike. Dr. Andrew E. Teschendorff is Head of the Computational Systems Genomics Lab at the CAS-MPG Partner Institute for Computational Biology, Shanghai, China, as well as an Honorary Research Fellow at the UCL Cancer Institute, University College London, UK. 000727104 650_0 $$aEpigenetics$$xMathematical models. 000727104 7001_ $$aTeschendorff, Andrew E.,$$eeditor. 000727104 830_0 $$aTranslational bioinformatics ;$$vVolume 7. 000727104 85280 $$bebk$$hSpringerLink 000727104 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-94-017-9927-0$$zOnline Access$$91397441.1 000727104 909CO $$ooai:library.usi.edu:727104$$pGLOBAL_SET 000727104 980__ $$aEBOOK 000727104 980__ $$aBIB 000727104 982__ $$aEbook 000727104 983__ $$aOnline 000727104 994__ $$a92$$bISE