Customer Reviews

Microarray Bioinformatics

5 star:		(4)
4 star:		(2)
3 star:		(1)
2 star:		(1)
1 star:		(0)

 

 

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.

This book describes basic concepts and procedures for those who are new to microarray. I'd recommend that a reader should use this book to grasp what microarray is. You won't be able to know anything in depth from this book but it will be nice to have this if you have trouble in understanding a more challenging book. Once you read this book, please go ahead and read another book since this book doesn't tell you everything about microarray. It's just a basic overview... i was glad that I used this book as my first microarray textbook....

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.

I'm not a biologist but became curious about the microarray technology. Although the book seems to cover the important aspects (as far as I can tell from browsing), it managed to annoy me. The author did not make effort to provide something very basic like a clear vocabulary.

Example: he starts using "spot" and "feature" without making effort to explain what they mean in the context of microarrays. At times it seems he treats them as synonyms which is confusing. I consulted the index hoping to find somewhere precise definition of these terms but to no avail. At the end, I had to go to Wikipedia and various other pages which did the job but then if you have to use internet to understand the book than why not just get everything from the web and save the money for the book?

Noting that the target audience are novices in the area of microarrays (experts won't find anything valuable here), the book does a poor job of serving them. To recap: "Nice try. Could do better"

This is an excellent introduction to microarray analysis. It is great at explaining the theory behind normalization, clustering, and dimensionality reduction without getting hung up on the statistics behind it. If you are looking for an exhaustive statistical treatment on the topic, this is not the book. But it will give you excellent background on these techniques that make reading statistical papers on the topic much easier for the non-statistics biologist.

Highly recommended.

Without question this short paperback is a nifty little text. What it does is provide the beginner with a basic brief overview in covering all major aspects of microarrays.

What you have to keep in mind is this book is intended for those who want a brief overview of all aspects of microarrays. Its a "forest for the trees" book on microarrays. The writing is very good and easy to follow, and its a great introductory text and reasonably priced.

Regardless of ones formal training, (e.g. Biology, Statistics, Computer Science, ... , health science) I think it would make an excellent little basic reference on ones bookshelf or to just have around in the lab for undergraduates/beginning graduate students.

Bottomline: If you prefer to learn things by starting at the start and not at the end then consider this book; Indeed its a great starter book to get your feet a little wet before jumping in over your head to the more gnarly stuff.

This book is written clearly, which also means it doesn't touch too deep. I believe it's mainly useful for biologists who want to get a brief and application oriented introduction, but not for the researchers that want to improve the technology.

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.