Statistical Analysis in Proteomics
This valuable collection aims to provide a collection of frequently used statistical methods in the field of proteomics. Although there is a large overlap between statistical methods for the different ‘omics’ fields, methods for analyzing data from proteo
- PDF / 11,473,671 Bytes
- 310 Pages / 504.63 x 737.01 pts Page_size
- 45 Downloads / 234 Views
Klaus Jung Editor
Statistical Analysis in Proteomics
METHODS
IN
MOLECULAR BIOLOGY
Series Editor John M. Walker School of Life and Medical Sciences University of Hertfordshire Hatfield, Hertfordshire, AL10 9AB, UK
For further volumes: http://www.springer.com/series/7651
Statistical Analysis in Proteomics
Edited by
Klaus Jung Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany
Editor Klaus Jung Department of Medical Statistics University Medical Center Göttingen Göttingen, Germany
ISSN 1064-3745 ISSN 1940-6029 (electronic) Methods in Molecular Biology ISBN 978-1-4939-3105-7 ISBN 978-1-4939-3106-4 (eBook) DOI 10.1007/978-1-4939-3106-4 Library of Congress Control Number: 2015952312 Springer New York Heidelberg Dordrecht London © Springer Science+Business Media New York 2016 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Cover illustration: For the complete image, please see Figure 2 of Chapter 3. Printed on acid-free paper Humana Press is a brand of Springer Springer Science+Business Media LLC New York is part of Springer Science+Business Media (www.springer.com)
Preface Among the high-throughput technologies that are currently used in biomedical research, those used in proteomics are perhaps the oldest. While mass spectrometry and 2-D gel electrophoresis were already used in the 1980s for simultaneous measuring of the abundance of multiple proteins, statistical methods for the analysis of high-throughput data experienced their great evolution first with the development of DNA microarrays in the mid-1990s. Although there is a large overlap between statistical methods for the different “omics” fields, methods for analyzing data from proteomics experiments need their own specific adaptations. Therefore, the aim of this book is to provide a collection of frequently used statistical methods in the field of proteomics. This book is designated to statisticians who are involved in the planning and analysis of proteomics experiments
Data Loading...
