Statistical Analysis of Next Generation Sequencing Data

Somnath Datta (u. a.)

ISBN 10: 3319379054 / ISBN 13: 9783319379050

Published by Springer, 2016

About this Item

Statistical Analysis of Next Generation Sequencing Data | Somnath Datta (u. a.) | Taschenbuch | Frontiers in Probability and the Statistical Sciences | xiv | Englisch | 2016 | Springer | EAN 9783319379050 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Seller Inventory # 111862040

Bibliographic Details

• Title: Statistical Analysis of Next Generation Sequencing Data
• Publisher: Springer
• Publication Date: 2016
• Language: English
• ISBN 10: 3319379054
• ISBN 13: 9783319379050
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 23D millimeters 235 millimeters width by 155 millimeters height by 23 millimeters depth
• Weight: 756 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Next Generation Sequencing (NGS) is the latest high throughput technology to revolutionize genomic research. NGS generates massive genomic datasets that play a key role in the big data phenomenon that surrounds us today. To extract signals from high-dimensional NGS data and make valid statistical inferences and predictions, novel data analytic and statistical techniques are needed. This book contains 20 chapters written by prominent statisticians working with NGS data. The topics range from basic preprocessing and analysis with NGS data to more complex genomic applications such as copy number variation and isoform expression detection. Research statisticians who want to learn about this growing and exciting area will find this book useful. In addition, many chapters from this book could be included in graduate-level classes in statistical bioinformatics for training future biostatisticians who will be expected to deal with genomic data in basic biomedical research, genomic clinical trials and personalized medicine.

About the editors:

Somnath Datta is Professor and Vice Chair of Bioinformatics and Biostatistics at the University of Louisville. He is Fellow of the American Statistical Association, Fellow of the Institute of Mathematical Statistics and Elected Member of the International Statistical Institute. He has contributed to numerous research areas in Statistics, Biostatistics and Bioinformatics.

Dan Nettleton is Professor and Laurence H. Baker Endowed Chair of Biological Statistics in the Department of Statistics at Iowa State University.  He is Fellow of the American Statistical Association and has published research on a variety of topics in statistics, biology and bioinformatics.

About the Author

About the editors:

Somnath Datta is Professor and Vice Chair of Bioinformatics and Biostatistics at the University of Louisville. He is Fellow of the American Statistical Association, Fellow of the Institute of Mathematical Statistics, and Elected Member of the International Statistical Institute. He has contributed to numerous research areas in Statistics, Biostatistics and Bioinformatics.

Dan Nettleton is Professor and Laurence H. Baker Endowed Chair of Biological Statistics in the Department of Statistics at Iowa State University.  He is Fellow of the American Statistical Association and has published research on a variety of topics in statistics, biology, and bioinformatics.