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Academic & Professional Books  Organismal to Molecular Biology  Biochemistry & Molecular Biology

Design and Analysis of DNA Microarray Investigations

Handbook / Manual
By: RM Simon, EL Korn, LM McShane, MD Radmacher, GW Wright and Y Zhao
199 pages, 58 illus
Publisher: Springer Nature
Design and Analysis of DNA Microarray Investigations
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  • Design and Analysis of DNA Microarray Investigations ISBN: 9780387001357 Hardback Jan 2004 Not in stock: Usually dispatched within 1-2 weeks
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About this book Contents Customer reviews Related titles

About this book

Discusses the analysis of gene expression profile data from DNA microarray studies and the design of such studies. The book addresses design and analysis issues for both of the major classes of DNA microarrays, the cDNA microarrays and the oligonucleotide arrays. This book provides an authoritative review of the methods available and presents it in a manner that is intelligible to biologists

Contents

Objectives of DNA Microarray Studies * Biological Background and DNA Microarray "Technology * Design of DNS Microarray Experiments * Image Analysis * Normalization and Filtering of Array Data and Evaluating Quality of Spots and Arrays * Comparing Individual RNA Samples * Unsupervised Methods for Discovering Structure * Supervied Methods for Distinguishing Phenotypes, Classes, or Outcome * Statistical Methods for Controlling Error Rates of Multiple Comparisons

Customer Reviews

Handbook / Manual
By: RM Simon, EL Korn, LM McShane, MD Radmacher, GW Wright and Y Zhao
199 pages, 58 illus
Publisher: Springer Nature
Media reviews

From the reviews: "This book gives a welcome introduction to microarray data and its analysis. Such analyses have been performed for many years, but only recently are new investigators able to read about the topic in such a concise and well-written format." Journal of Biopharmaceutical Statistics, Issue #4, 2005 "I enjoyed it and recommend it for anyone working in this area." Short Book Reviews of the ISI, April 2005 "This is a book to get your biological collaborators to read, because it provides good statistical perspectives on the design of experiments and on other methodologies needed to design and analyze microarray experiments. The treatment is straightforward, but not simple." Journal of the American Statistical Association, June 2005 "The book presents the basics of microarray technology and follows with chapters on designing experiments and processing the scanned images. Further to this, it provides an introduction to selecting appropriate analysis techniques that will result in valid answers. ! The understanding of many of the statistical applications is enhanced by the inclusion of several real-world medical datasets as examples." (Rebecca E. Walls) "A very good overview of the issues and techniques, suitable for a non-specialist readership that would be interested to embark on microarray studies. Throughout, the authors discuss both spotted cDNA arrays and oligonucleotide arrays ! which adds further merit to this book. ! A great asset of this book is that all the example data are freely available for analysis ! . an excellent introduction to all aspects of microarray analyses ! a very good read ! ." (Dirk -- Jan De Koning, Genetical Research, Vol. 84, 2004) "This book presents a concise overview of many useful statistical approaches to microarray data ! . This broad range of topics makes the book unique and useful. ! this book is a valuable resource for microarray experimenters. I enjoyed it and recommend it for anyone working in this area." (R. Tibshirani, Short Book Reviews, Vol. 25(1), 2005) "This book is concerned with methods of analyzing data obtained from DNA microarray experiments. ! The book is written for biologists without a strong statistical background, and also for computer scientists and statisticians interested in being collaborators in studies utilizing microarrays." (Alexander Mitrophanov, Zentralblatt MATH, Vol. 1039(8), 2004) "The small number of noisy microarrays relative to the large number of genes presents a challenge to biologists using this technology. This book aims to aid the biologist in solving some of these problems ! . It largely achieves this aim. ! the chapters are logically integrated and perfectly consistent with each other. ! describes, overall, a sensible approach to microarray analysis. ! the authors have done an excellent job in presenting sensible statistical methodology to the biological community." (Ernst Wit, Human Genetics, Vol. 1(6), November "For the biomedical researcher, it promises an introduction and survey to the principles of biometrical thinking ! . For the biometrician, it describes typical experimental approaches, data structures, design and analysis problems ! . We are convinced that this book is a must for all readers who are interested in the design, conduct and analysis of microarray gene expression experiments. It will certainly impact on the necessary communication between researchers of all type engaged in this truly cross disciplinary subject." (Dirk Repsilber and Andreas Ziegler, Metrika, Vol. 64, 2006) "Analysis of data arising from microarray experiments is one of the very exciting areas in statistics these days. ! it is important to have text books that can serve the dual purpose of catering basic biology related to microarray experiments to statisticians and exposing to biologists the basic statistical techniques needed for designing microarray experiments and analyzing data generated from such experiments. ! This book will be quite useful for biostatisticians and biologists interested in microarray experiments and related data analysis." (Probal Chaudhuri, Sankhya, Vol. 67 (1), 2005) "Microarray experiments are rapidly growing in popularity for their ability to analyze DNA samples with relative ease. This book, penned by a collection of current and former members of the Biometric Research Branch at the National Cancer Institute, offers a concise yet comprehensive guide to designing and analyzing such experiments. ! The book is aimed at biologists with limited statistical knowledge ! ." (Journal of Applied Statistics, Vol. 32 (4), 2005)

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