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Statistics and Data Analysis for Microarrays Using R and Bioconductor, Second Edition (Chapman & Hall/CRC Mathematical and Computational Biology) Hardcover – December 6, 2011

ISBN-13: 978-1439809754 ISBN-10: 1439809755 Edition: 2nd

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Product Details

  • Series: Chapman & Hall/CRC Mathematical and Computational Biology (Book 4)
  • Hardcover: 1036 pages
  • Publisher: Chapman and Hall/CRC; 2 edition (December 6, 2011)
  • Language: English
  • ISBN-10: 1439809755
  • ISBN-13: 978-1439809754
  • Product Dimensions: 9.3 x 6.2 x 1.9 inches
  • Shipping Weight: 4.4 pounds
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (10 customer reviews)
  • Amazon Best Sellers Rank: #497,955 in Books (See Top 100 in Books)

Editorial Reviews

Review

Praise for the First Edition
The book by Draghici is an excellent choice to be used as a textbook for a graduate-level bioinformatics course. This well-written book with two accompanying CD-ROMs will create much-needed enthusiasm among statisticians.
Journal of Statistical Computation and Simulation, Vol. 74

I really like Draghici's book. As the author explains in the Preface, the book is intended to serve both the statistician who knows very little about DNA microarrays and the biologist who has no expertise in data analysis. The author lays out a study plan for the statistician that excludes 5 of the 17 chapters (4-8). These chapters present the basics of statistical distributions, estimation, hypothesis testing, ANOVA, and experimental design. What that leaves for the statistician is the three-chapter primer on microarrays and image processing, plus all of the data analysis tools specific to the microarray situation. … it includes two CDs with trial versions of several specialised software packages. Anyone who uses microarray data should certainly own a copy.
Technometrics, Vol. 47, No. 1, February 2005

About the Author

Sorin Drăghici holds the Robert J. Sokol MD Endowed Chair in Systems Biology in the Department of Obstetrics and Gynecology, and is a professor in the Department of Clinical and Translational Science and the Department of Computer Science, as well as the head of the Intelligent Systems and Bioinformatics Laboratory at Wayne State University. He is also the chief of the Bioinformatics and Data Analysis Section in the Perinatology Research Branch of the National Institute for Child Health and Development. A senior member of IEEE, Dr. Drăghici is an editor of IEEE/ACM Transactions on Computational Biology and Bioinformatics, Journal of Biomedicine and Biotechnology, and International Journal of Functional Informatics and Personalized Medicine. He earned a Ph.D. in computer science from the University of St. Andrews, UK.

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Customer Reviews

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Throughout the book, very essential snippets of R code are revealed.
Rebecca L. Tagett
If you have a foundation in statistics and need a primer on genetic biology and the technology used to analyze genomic data, this book is wonderful.
iERG
Next the book covers statistics in a way that I found to be very readable.
George G. Roberts

Most Helpful Customer Reviews

7 of 7 people found the following review helpful By Rebecca L. Tagett on February 19, 2012
Format: Hardcover Verified Purchase
This book is extremely rich yet readable. It covers a lot of different topics, and chapters can be read in order or referred to as needed.
However, if you take the time to read it through carefully, you will enjoy yourself, because the author is a master of pedagogy, and often humorous.

While expression microarrays are the platforms covered by this book, most of the material has much broader application beyond that. Cell biology, R, statistics, experiment design, molecular pathways, and machine learning are all covered. Even if you don't work with microarrays, there is something in this book for you, anyway you should know the basics of microarray analysis.

Computer scientists or other non biologists may want to start at the beginning, which is an introduction to the cell and its basic mechanisms. It may seem like a lot of memorization and daunting to those who have never learned biology, but this chapter is well written with plenty of color images. It gives all of the fundamental biology needed to understand microarrays.

The author knows which topics need to be covered in more depth than other authors are generally willing to do. I especially appreciated the section on degrees of freedom. If you never really had a grasp on this topic (but used it anyway) you will be grateful for section 8.4!

Another chapter that I especially appreciated was "Experiment Design", which is so critical to any scientist of molecular biology and bioinformatics. How many of us in bioinformatics have been asked to analyze data from poorly designed experiments?
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4 of 4 people found the following review helpful By minijen on June 16, 2012
Format: Hardcover
Thank you, Sorin. It is a fantastic book, funny, easy to follow and extremely useful for my work.
I have a very strong biological/biochemical background (PhD + postdoc), but I switched to bioinformatics several years ago. I've never got any formal training in bioinformatics, just reading a lot of books, publications, taking courses, attending lectures and talking to experts. This book has structured and organized my knowledge, cleared up some terms and conceptions, advanced my R skills.
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3 of 3 people found the following review helpful By Leandro de Mattos Pereira on May 10, 2012
Format: Hardcover Verified Purchase
Very good this book, excellent! it covers various aspects of the basic statistics and methods of data mining and steps for data microarray analysis.
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1 of 1 people found the following review helpful By Debra Klopfenstein on March 16, 2014
Format: Hardcover Verified Purchase
What a great book. The author is an excellent teacher who is skilled in transferring his in-depth knowledge to people unfamiliar with the material who wish to learn. The book is engaging and highly readable. In his short, but densly-packed chapter on GO-Terms, I learned more from him in a couple hours than I did from TAs in a 3-hour class augmented by many additional hours of my own independent searching on the web to "fill in the gaps". Fantastic book!
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1 of 1 people found the following review helpful By Manuel Duval on December 17, 2013
Format: Hardcover
This is the must-read textbook for any one involved in any shape or form in genomics research. It is a self-contained reference book in a sense that all prerequisites are laid down (e.g. inferential statistics). Regardless of her/his background, the reader will be equipped with both the theoretical and technical skills required for analysing and interpreting the output of genome-wide RNA quantification methods. I not only enjoyed and greatly benefited from it; I recommend it to my own students enrolled in our bioinformatics program.
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