國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Computational and statistical epigen...

SpringerLink (Online service)

Computational and statistical epigenomics

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Computational and statistical epigenomicsedited by Andrew E. Teschendorff.
其他作者:	Teschendorff, Andrew E.
出版者:	Dordrecht :Springer Netherlands :2015.
面頁冊數:	v, 217 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	EpigeneticsMathematical models.
電子資源:	http://dx.doi.org/10.1007/978-94-017-9927-0
ISBN:	9789401799270 (electronic bk.)

Computational and statistical epigenomics
Computational and statistical epigenomics[electronic resource] /edited by Andrew E. Teschendorff. - Dordrecht :Springer Netherlands :2015. - v, 217 p. :ill., digital ;24 cm. - Translational bioinformatics,v.72213-2775 ;. - Translational bioinformatics ;v.2.

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 (electronic bk.)

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

724566
Epigenetics
--Mathematical models.

LC Class. No.: RB155

Dewey Class. No.: 616.042

Computational and statistical epigenomics
LDR:02372nmm a2200325 a 4500 001 468839
003 DE-He213
005 20151203160449.0
006 m d
007 cr nn 008maaau
008 160118s2015 ne s 0 eng d
020 $a 9789401799270 (electronic bk.)
020 $a 9789401799263 (paper)
024 7 $a 10.1007/978-94-017-9927-0 $2 doi
035 $a 978-94-017-9927-0
040 $a GP $c GP
041 0 $a eng
050 4 $a RB155
072 7 $a PSD $2 bicssc
072 7 $a UB $2 bicssc
072 7 $a SCI056000 $2 bisacsh
082 0 4 $a 616.042 $2 23
090 $a RB155 $b .C738 2015
245 0 0 $a Computational and statistical epigenomics $h [electronic resource] / $c edited by Andrew E. Teschendorff.
260 $a Dordrecht : $b Springer Netherlands : $b Imprint: Springer, $c 2015.
300 $a v, 217 p. : $b ill., digital ; $c 24 cm.
490 1 $a Translational bioinformatics, $x 2213-2775 ; $v 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 Epigenetics $x Mathematical models. $3 724566
650 1 4 $a Life Sciences. $3 273679
650 2 4 $a Bioinformatics. $3 194415
650 2 4 $a Computer Appl. in Life Sciences. $3 274180
650 2 4 $a Molecular Medicine. $3 273932
650 2 4 $a Epidemiology. $3 191577
700 1 $a Teschendorff, Andrew E. $3 724565
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Translational bioinformatics ; $v v.2 $3 591971
856 4 0 $u http://dx.doi.org/10.1007/978-94-017-9927-0
950 $a Biomedical and Life Sciences (Springer-11642)