| View Larger Image | Microarray Gene Expression Data Analysis: A Beginner's Guide | Paperbackby Helen Causton (Author), John Quackenbush (Author), Alvis Brazma (Author)
| List Price: | $86.99 | | Price: | $72.90 | | You Save: | $14.09 (16%) | | | Available: | Usually ships in 24 hours |
| | Binding: | Paperback | | Publisher: | Wiley-Blackwell | | Edition: | 1st Edition | | Page Count: | 176 Pages | | Publication Date: | April 25, 2003 | | Sales Rank: | 923,812rd |
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EDITORIAL REVIEWS |
Product Description
This guide covers aspects of designing microarray experiments and analysing the data generated, including information on some of the tools that are available from non-commercial sources. Concepts and principles underpinning gene expression analysis are emphasised and wherever possible, the mathematics has been simplified. The guide is intended for use by graduates and researchers in bioinformatics and the life sciences and is also suitable for statisticians who are interested in the approaches currently used to study gene expression. Microarrays are an automated way of carrying out thousands of experiments at once, and allows scientists to obtain huge amounts of information very quickly Short, concise text on this difficult topic area Clear illustrations throughout Written by well-known teachers in the subject Provides insight into how to analyse the data produced from microarrays |
CUSTOMER REVIEWS (Average Customer Rating: 4.0 based on 2 reviews)
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A good introduction to the topic by calvinnme (Fredericksburg, Va)  4 Stars
May 20, 2007
Microarrays are a tool for monitoring gene expression levels for thousands of genes in parallel. This technology is very useful since patterns in the gene expression can be used for molecular characterization of phenomena that range from disease states and response to stimuli to the differences between cells of different types. The amount of information obtained from one microarray experiment can be large. These large amounts of information present new challenges in the areas of data storage, management, and analysis by biologists who are not accustomed to dealing with this much data. Also, the software used for data analysis is usually written by mathematicians and statisticians that have a minimum of training in biology.
This book addresses some of the issues faced by researchers who are beginning their first microarray experiments. It covers various aspects of designing and analyzing the results of microarray experiments. Microarrays are not limited to the study of gene expression, but this remains the most common use of the technology and therefore is the only use of arrays discussed here. This book attempts to explain the underlying concepts and principles routinely used in analysis of gene expression data. The book should be accessible by statisticians, computer scientists, and students of bioinformatics who want a grounding in the types of analysis currently used to study microarray data.
The book begins with an introductory chapter which is followed by three major chapters. As with any technology that has the capacity to detect small changes in a highly dynamic system, the underlying experimental design and the manner in which an experiment is conducted is critical for obtaining high quality data. Chapter two addresses these issues. The raw data from microarray experiments are images that must be transformed and organized into gene expression matrices. These transformations are the subject of chapter 3. Finally, in chapter 4, the common methods used for analyzing gene expression data matrices with the goal of obtaining new insights into biology are discussed. The book does a pretty good job of providing the reader with a general understanding of the nature of microarray data and how it can be analyzed. It was never meant to be a reference book or a comprehensive review, just a gentle introduction.
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Well written, short explanations but nevertheless understandable by Zac (USA) 4 Stars
July 05, 2005
Certainly, this book can not give a complete description of microarrays, neither from an experimental nor a theoretical side. Nevertheless, the issues presented and discussed provide the reader with a solid basis for more advanced studies.
In my opinion, this book is well written, the explanations given are descriptive and understandable and its overall organization is plausible. I recommend this book as an introduction for the analysis of microarray data, because it provides a good overview of existing methods in this field. A warning: This does not mean, that all these methods are thorougly expained! It just provides an overview!! If you want to learn, e.g., clustering methods, you should consult another book (probably no other book about microarrays but a decent book dealing only with data analysis in general or clustering methods...)
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