Microarray Bioinformatics

Features

• Cover Type: Paperback with 280 pages
• Published by: Cambridge University Press
• Edition: 1st Edition September 8, 2003
• Written in: English
• ISBN 10 Number: 052152587X
• ISBN 13 Number: 978-0521525879
• Book Dimensions: 9.9 x 6.8 x 0.7 inches
• Weighs: 11.2 ounces

Product Review
'The author does an great job of covering high-level analysis of microarray data [the book] provides the statistically naive biologist with a gentle introduction to the data transformations and manipulations needed to deal with microarrays, and the worked examples with publicly available data are well described great value for any budding arrayer '. Nature Genetics ' great and clearly written a pleasure to read.' 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.' Microbiology Today

Product Review
"excellent and clearly writtenconcise 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

Reader Reviews
This review is from: Microarray Bioinformatics (Hardcover) 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.