國立虎尾科技大學 |

Computational and Statistical Epigenomics

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Computational and Statistical Epigenomics/ edited by Andrew E. Teschendorff.
其他作者:	Teschendorff, Andrew E.
面頁冊數:	V, 217 p. 42 illus., 41 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Bioinformatics. -
電子資源:	https://doi.org/10.1007/978-94-017-9927-0
ISBN:	9789401799270

Computational and Statistical Epigenomics
Computational and Statistical Epigenomics[electronic resource] /edited by Andrew E. Teschendorff. - 1st ed. 2015. - V, 217 p. 42 illus., 41 illus. in color.online resource. - Translational Bioinformatics,72213-2775 ;. - Translational Bioinformatics,5.

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.

ISBN: 9789401799270

Standard No.: 10.1007/978-94-017-9927-0doiSubjects--Topical Terms:

583857
Bioinformatics.

LC Class. No.: QH324.2-324.25

Dewey Class. No.: 570.285

Computational and Statistical Epigenomics
LDR:02796nam a22004095i 4500 001 969014
003 DE-He213
005 20200701175343.0
007 cr nn 008mamaa
008 201211s2015 ne | s |||| 0|eng d
020 $a 9789401799270 $9 978-94-017-9927-0
024 7 $a 10.1007/978-94-017-9927-0 $2 doi
035 $a 978-94-017-9927-0
050 4 $a QH324.2-324.25
072 7 $a PSD $2 bicssc
072 7 $a SCI056000 $2 bisacsh
072 7 $a PSD $2 thema
072 7 $a UB $2 thema
082 0 4 $a 570.285 $2 23
245 1 0 $a Computational and Statistical Epigenomics $h [electronic resource] / $c edited by Andrew E. Teschendorff.
250 $a 1st ed. 2015.
264 1 $a Dordrecht : $b Springer Netherlands : $b Imprint: Springer, $c 2015.
300 $a V, 217 p. 42 illus., 41 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Translational Bioinformatics, $x 2213-2775 ; $v 7
520 $a 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.
650 0 $a Bioinformatics. $3 583857
650 0 $a Bioinformatics . $3 1253897
650 0 $a Computational biology . $3 1253898
650 0 $a Molecular biology. $3 583443
650 0 $a Epidemiology. $3 635923
650 2 4 $a Computer Appl. in Life Sciences. $3 593908
650 2 4 $a Molecular Medicine. $3 668353
700 1 $a Teschendorff, Andrew E. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1264604
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9789401799287
776 0 8 $i Printed edition: $z 9789401799263
776 0 8 $i Printed edition: $z 9789402403435
830 0 $a Translational Bioinformatics, $x 2213-2775 ; $v 5 $3 1258097
856 4 0 $u https://doi.org/10.1007/978-94-017-9927-0
912 $a ZDB-2-SBL
912 $a ZDB-2-SXB
950 $a Biomedical and Life Sciences (SpringerNature-11642)
950 $a Biomedical and Life Sciences (R0) (SpringerNature-43708)