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Statistical and Computational Pharmacogenomics (Chapman & Hall/CRC Interdisciplinary Statistics) Hardcover – August 8, 2008

ISBN-13: 978-1584888284 ISBN-10: 1584888288 Edition: 1st

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Product Details

  • Series: Chapman & Hall/CRC Interdisciplinary Statistics
  • Hardcover: 368 pages
  • Publisher: Chapman and Hall/CRC; 1 edition (August 8, 2008)
  • Language: English
  • ISBN-10: 1584888288
  • ISBN-13: 978-1584888284
  • Product Dimensions: 1 x 6.5 x 9.5 inches
  • Shipping Weight: 1.4 pounds (View shipping rates and policies)
  • Average Customer Review: 4.7 out of 5 stars  See all reviews (3 customer reviews)
  • Amazon Best Sellers Rank: #3,459,347 in Books (See Top 100 in Books)

Editorial Reviews

Review

… a statistically rigorous text that gives a systematic exposition of the subject of pharmacogenomics, the related analytical methods and the corresponding computational algorithms. … a good basis for further methodological, empirical and applied investigation into the field.
Statistics in Medicine, 2011, 30

This text is one of the first books written by statisticians and for statisticians who need to know the basics of genetic markers based on genomic mapping and haplotyping. … this book is a welcome addition that will help me learn pharmacogenomics to the extent that I need it to apply appropriate statistical methodology in microarray analysis and classification problems. … I can recommend it for the statisticians … . I also hope that it will be successful at getting the chemists, biologists, and geneticists interested in the important statistical methods and mathematical modeling described in this book.
—Michael R. Chernick, Technometrics, February 2011

This book covers advanced topics in statistical genetics focusing on applications of interest in pharmacogenomics. The difficulties in estimating haplotype frequencies and their effects on quantitative trait loci (QTLs) are covered in detail for a variety of experimental designs. … of most interest for statisticians working in the pharmaceutical area that need to incorporate genetic variables into consideration in their studies.
ISCB News, No. 50, December 2010

… [Pharmacogenomics] can address questions such as whether individuals with different versions of a gene are more or less likely to respond to a particular drug. However, Wu and Lin go well beyond this and discuss methods for relating genetic variation to dynamic pharmacokinetic and pharmacodynamic profiles of drugs. They refer to this as ‘functional mapping’. … One of the main clinical applications of these methods will be in predicting efficacy and toxicity of drugs, allowing treatment to be tailored to an individual’s genetic background, and this book makes a valuable contribution towards this.
Significance, June 2010

…a volume that can be recommended to both statisticians and life scientists. Yes, there’s plenty of heavy-duty math for the theory lovers, but there are also many sections of explanations for the biologist. These explanations are not highly theoretical and give the scientist a better understanding of what the analysis is doing and why it is needed.
—John A. Wass, Ph.D., Scientific Computing, 2009

About the Author

University of Florida, Gainsville, USA Duke Clinical Research Institute, Durham, North Carolina, US University of Kent, UK University of Copenhagen, Denmark Utrecht University, The Netherlands University of California, Berkeley, USA

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Most Helpful Customer Reviews

2 of 2 people found the following review helpful By Michael R. Chernick on June 28, 2010
Format: Hardcover
I have provided a more detailed review for Technometrics but I would like to explain here why I like the book and encourage biostatisticians to read it and keep it on their book shelf.

This text is one of the first books written by statisticians for statisticians who need to know the basics of genetic markers based on genomic mapping and haplotyping. Since I have worked for many years and current work in the pharmaceutical industry, I know that as we learn more and more about the human genome and the processes that create individual genetic responses we are learning how to identify subgroups that respond well to a drug or have fewer side effects. If genetic markers can accurately identify individuals that respond well to a drug as well as those that do not, more drugs may be come available that can treat a subset of the population that has a certain disease without creating hazardous side effect. Often drugs have failed to reach market because of serious complications found on a small but significant portion of the population even though they could potential benefit many others. Getting more drugs to market that are safe and effective in a targeted population is the goal that has great potential and is beginning to bear fruit.

The authors' goals are (1) to summarize in one place the scattered literature that has developed over the past 5 years in a very readable way, (2) to expose the statistician who works in the pharmaceutical field the underlying theory that motivates the statistical methods that are employed, (3) to show the biologists, geneticists, chemists, and clinicians the value of some very powerful statistical techniques that encompass functional mappping. I can be very positive about the authors' acheiving goals 1 and 2. Goal 3 is difiuclt for me to access since I am a statistician and not a biologist, geneticist or chemist who might have limited statsistcal background.
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By maria pilar sanchez on November 20, 2012
Format: Hardcover Verified Purchase
A issue very important for pharmacist, treated in a comprehensively way. I like a second part with specifics of pharmacogenetics analysis.
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Format: Hardcover
Do not read that book if you don't like mathematics, it has detailed all the formulas to help compute in that field
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