| View Larger Image | The Analysis of Gene Expression Data | Hardcoverby Giovanni Parmigiani (Editor), Elizabeth S. Garett (Editor), Rafael A. Irizarry (Editor), Scott L. Zeger (Editor)
| List Price: | $109.00 | |
| | Binding: | Hardcover | | Publisher: | Springer | | Edition: | 1st Edition | | Page Count: | 504 Pages | | Publication Date: | April 08, 2003 | | Sales Rank: | 1,165,165st |
|
EDITORIAL REVIEWS |
Product Description
This book presents practical approaches for the analysis of data from gene expression microarrays. Each chapter describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. Methods cover all aspects of statistical analysis of microarrays, from annotation and filtering to clustering and classification. Chapters are written by the developers of the software. All software packages described are free to academic users. The book includes coverage of various packages that are part of the Bioconductor project and several related R tools. The materials presented cover a range of software tools designed for varied audiences. Some chapters describe simple menu-driven software in a user-friendly fashion, and are designed to be accessible to microarray data analysts without formal quantitative training. Most chapters are directed at microarray data analysts with master-level training in computer science, biostatistics or bioinformatics. A minority of more advanced chapters are intended for doctoral students and researchers. The team of editors is from the Johns Hopkins Schools of Medicine and Public Health and has been involved with developing methods and software for microarray data analysis since the inception of this technology. Giovanni Parmigiani is Associate Professor of Oncology, Pathology and Biostatistics. He is the author of the book on "Modeling in Medical decision Making," a fellow of the ASA, and a recipient of the Savage Awards for Bayesian statistics. Elizabeth S. Garrett is Assistant Professor of Oncology and Biostatistics, and recipient of the Abbey Award for statistical education. Rafael A Irizarry is Assistant Professor of Biostatistics, and recipient of the Noether Award for non-parametric statistics. Scott L. Zeger is Professor and chair of Biostatistics. He is co-author of the book "Longitudinal Data Analysis," a fellow of the ASA and recipient of the Spiegelman Award for public health statistics. |
CUSTOMER REVIEWS (Average Customer Rating: 3.5 based on 2 reviews)
|
Not the best but still good by Falling Maple (Boston, MA)  4 Stars
May 11, 2004
Some of the software commands in this book are already outdated, esp. in bioconductor. If you need to analyze a microarray data and you do not know much about the algorithms, this book gives an overview what is available. To get more insights about the theory, can check out EXPLORATORY AND ANALYSIS OF DNA MICROARRAY AND PROTEIN ARRAY or the research papers published by the authors. There is no one best method for analyzing microarray data, so don't expect a miracle from this book or any others.
| |
Maybe good, just not for me by wiredweird (Earth, or somewhere nearby)  3 Stars
January 15, 2004
I thumbed through a copy of this book, but I admit I haven't read it. It just doesn't meet my needs.It's about a number of software packages available for analyzing microarray and related kinds of data. Different sections of the book seemed to range from brief surveys to fairly detailed how-to chapters, by different authors, describing different packages.I'm interested in microarray data analysis, but I want the more theoretical material - the basic computations and the principles behind them. Details of statistical and analytic techniques were too scattered, if present at all, to hold my interest. If you want the biological or medical answers from the programs without worrying too much about how they're derived, maybe this book will help you. Or maybe not, I'm not the one to judge - three stars, just because I had to give some number.
| |
SIMILAR PRODUCTS |
| Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Statistics for Biology and Health)
by Robert Gentleman (Editor), Vincent Carey (Editor), Wolfgang Huber (Editor), Rafael Irizarry (Editor), Sandrine Dudoit (Editor)
Bioconductor is a widely used open source and open development software project for the analysis and comprehension of data arising from high-throughput experimentation in genomics and molecular biology. Bioconductor is rooted in the open source statistical computing environment R. This volume's coverage is broad and ranges across most of the key capabilities of the Bioconductor project, including importation and preprocessing of high-throughput data from microarray, proteomic, and...
| 
| Advanced Analysis of Gene Expression Microarray Data (Science, Engineering, and Biology Informatics)
by Aidong Zhang (Author)
This book focuses on the development and application of the latest advanced data mining, machine learning, and visualization techniques for the identification of interesting, significant, and novel patterns in gene expression microarray data. Biomedical researchers will find this book invaluable for learning the cutting-edge methods for analyzing gene expression microarray data. Specifically, the coverage includes the following state-of-the-art methods: gene-based analysis - the latest novel...
| 
| Design and Analysis of DNA Microarray Investigations
by Richard M. Simon (Author), Edward L. Korn (Author), Lisa M. McShane (Author), Michael D. Radmacher (Author), George W. Wright (Author), Yingdong Zhao (Author)
This book discusses the analysis of gene expression profile data from DNA micorarray studies and the design of such studies. The book will address design and analysis issues for both of the major classes of DNA microarrays, the cDNA microarrays and the oligonucleotide arrays. DNA microarrays are a new technology that is revolutionizing biological and biomedical research. Most biologists are trying to analyze their own data using a variety of commercial and public domain software. This book will...
| 
| Statistical Methods in Bioinformatics: An Introduction (Statistics for Biology and Health)
by Warren J. Ewens (Author), Gregory Grant (Author)
Advances in computers and biotechnology have had an immense impact on the biomedical fields, with broad consequences for humanity. Correspondingly, new areas of probability and statistics are being developed specifically to meet the needs of this area. There is now a necessity for a text that introduces probability and statistics in the bioinformatics context. This book also describes some of the main statistical applications in the field, including BLAST, gene finding, and evolutionary...
| 
| R Programming for Bioinformatics (Chapman & Hall/Crc Computer Science & Data Analysis)
by Robert Gentleman (Author)
|
|
|
