... The stated audience for this book is M.S. and Ph.D. students in bioinformatics, machine intelligence, applied statistics, biostatistics, computer science, and related areas. ... a well-written collection from multiple authors that I recommend for the intended audience. Several chapters include exercises. -Technometrics, November 2009, Vol. 51, No. 4 ...a good text/reference book that summarizes the latest developments in the interface between bioinformatics and machine learning and offer[s] a thorough introduction to each field. ... One of the strengths of this book is the clear notation with a mathematical and statistical flavor, which will be attractive to Biometrics readers, especially to those new to statistical learning and data mining. It is also very readable for a variety of interested learners, researchers, and audiences from various backgrounds and disciplines. ... -Biometrics, March 2009 ... a well-structured book that is a good starting point for machine learning in bioinformatics. ... Using many popular examples, the statistical theory becomes comprehensible and bioinformatics examples motivate [readers] to apply the concepts to real data. -Markus Schmidberger, Journal of Statistical Software, November 2008