Statistical and Computational Pharmacogenomics

Reviews / Votes

... 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