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Microarray Bioinformatics, by Dov Stekel
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This book is a comprehensive guide to all of the mathematics, statistics and computing you will need to successfully operate DNA microarray experiments. It is written for researchers, clinicians, laboratory heads and managers, from both biology and bioinformatics backgrounds, who work with, or who intend to work with microarrays. The book covers all aspects of microarray bioinformatics, giving you the tools to design arrays and experiments, to analyze your data, and to share your results with your organisation or with the international community. There are chapters covering sequence databases, oligonucleotide design, experimental design, image processing, normalisation, identifying differentially expressed genes, clustering, classification and data standards. The book is based on the highly successful Microarray Bioinformatics course at Oxford University, and therefore is ideally suited for teaching the subject at postgraduate or professional level.
- Sales Rank: #3908611 in eBooks
- Published on: 2003-09-08
- Released on: 2003-09-08
- Format: Kindle eBook
Review
"...excellent and clearly written...concise and most informative, a pleasure to read. It should be examined by anyone interested in this means of analysis."
ASM News
"The book would be ideal for biologists who wish to gain a grasp of the different analysis techniques available to the microarray user."
Society for General Microbiology
Most helpful customer reviews
13 of 15 people found the following review helpful.
Microarrays Lite
By wiredweird
It just doesn't have the detail I wanted.
There's a lot to like here. Stekel covers everything, starting with selecting the probes and printing the arrays. Next comes raw array analysis - scanning, image processing, and measuring the effects of the array itself on the results. That covers the first six chapters. The next three go over analysis of the result, one more chapter covers experimential design, and the last chapter discusses storing, labelling, and sharing the data. Some of those topics, like experiment design, address issues that most other authors neglect.
Still, I came away feeling that I had read only half of each chapter. Going back, it turned out that I hadn't missed anything that really was there. I missed a lot, though. For example, probe selection includes a discussion of self-hybridization - good stuff. It stopped short of giving me any clear idea how much self-complementarity is too much. It mentioned DNA melting points, but without enough information for me to understand what is really melting, or how or why to choose one melting point over another. Handling of raw array data discussed Loess regression as a way to cancel out process differences across a single array. Again, it's good stuff, but what exactly is a Loess regression? Expression analysis mentions Spearman correlation as an alternative to Pearson correlation - it give Pearson's formulas, but not Spearman's. Later, when the author does give a "formula" for selecting sample sizes, it turns out to be some macro reference for some stat package. Throughout the book, I felt the same lack: I learned the names of many things, but not what they really are.
Maybe this book is OK for a first introduction. If you've had that introduction and want to take the second steps, this book probably won't meet your needs.
2 of 4 people found the following review helpful.
A Good Book for Microarray Bioinformatics
By A Customer
I rate this book a 5 star because I believe this book is one of best bioinformatics books which make it possible for the biologists to understand the bioinformatic tools inside of microarray technology. For me the most useful chapters include Sequence Databases for Microarrays, Computer Design of Oligonucleotide Probes, Normalisation, Measuring and Quantifying Microarray Variability, Analysis of Differentially Expressed Genes. As a three-years microarray user, I still get a lot information after I read this book. However, no any bioinformatic books are perfect and complete. There are also some limitations in this book. The author sometimes did not provide detailed information on some biostatistic analysis tools and only provided some references for reading. Since a lot of bioinformatic tools are still in the trial stage and need to be improved, we can not blame the author for the incompleteness.
As a 250-pages bioinformatics book, I believe, this book is very informative and useful for microarray users and biologists who are tired of understanding the abstract biostatistic equations.
0 of 0 people found the following review helpful.
Very good introduction to microarray bioinformatics
By postdoc
This is a very clearly written and easy to read introduction to microarray bioinformatics. It builds a basic basis of knowledge in a very short time, so it is a great start for beginners in the field. By the end of the book you also have a pretty clear sense of what you might want to read in more depth. It does not treat any of the subjects in great detail, but does have reading suggestions for each chapter, including books and original papers. Also, the bioinformatics concepts are explained in a very logical and easy to grasp manner, so the biologist or physician with no computational background will find it particularly useful.
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