Customer Reviews

DNA Microarrays and Gene Expression: From Experiments to Data Analysis and Modeling

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

 

 

This book tries to combine a practical and theoretical point of view concering microarray expermiments and the data analyis thereof. This is a very honourable goal. Unfortunatelly, it fails. An indicator for this can already be seen in the low number of pages. This book has less than 140 pages (I exclude the last chapter and the appendix). It is clear, that it is impossible to discuss in detail this topic in this limited number of pages. Hence, during reading the chapters one gets the feeling, that one reads short essays which are stringed together. At no point the authors go into detail but give only a short idea and references.

I see no reason, why I should recommend this book to anyone. It is in its current form just immature. My prediction: There will be no second edition because even its basic substance is very weak.

Some words to the last chapter (systems biology). This is indeed the most interesting and best chapter of the book (35 pages) without going into details as the rest of the book. I think according to this chapter one realize under which premise this book was written. Unfortunatelly, combining buzz worlds in short essays is not enough for a good book. Sorry guys, I think you can do better!

"Very complete : covers both the experimental and the computational methods with specific examples. Written by two top scientists who have worked hard at complementing each other's strengths. I particularly enjoyed the last chapter on Systems Biology which provides a masterful overview of current resaerch trends."

This book has a good balance between experimental and computational methods. It provides a description of DNA microarray technologies, experimental protocols, and the multiple sources of noise and variability. The book contains an insightful overview of the computational issues and available algorithms for data analysis from differential expression, to dimensionality reduction and visualization (e.g. PCA), to clustering (e.g. hierarchical). New methods are described to gether with a good overview of available software, data bases, web sites, and other resources, as well as several "walk through" examples. I particularly enjoyed the last chapter on Systems Biology.