Bioinformatics concerns the application of information technology to the study and analysis of biological and in particular genetic, data. The field has been further developed by the increase in DNA data generation. This has led to the generation of massive data sets. However, students of bioinformatics should not simply restrict their interests to computer science theory. Substantial training in various areas of biology, such as molecular genetics, is essential for a deeper understanding of the subject. This book provides an introductory account of probability theory, statistics and stochastic process theory.
From the reviews:
SIAM REVIEW
"...the book covers an impressive array of topics and provides ample material for a two-semester graduate course...Where possible the concepts are illustrated with interesting examples from bioinformatics, and many of these examples, together with the exercises at the end of each chapter, could be used to liven up any introductory course on discrete probability...My favorite feature of the book is the scattering throughout of clear and very detailed descriptions of several commonly used procedures from bioinformatics, each of which might otherwise require a tedious trawl through the primary literature to locate...I recommend the book for those who want to know more about statistics in bioinformatics as it is currently practiced and as a very helpful resource for anyone preparing a course in bio informatics or computational biology."
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
"The book is generally well written, well organized and worthwhile...topics are well chosen to give a sense of the problems and approaches used in bioinformatics...successfully fills the gap that it was intended to fill. The highlights of this book are the chapters that actually cover bioinformatics. These are well written and at a good level for an introductory course. These chapters would also make a good reading for statisticians looking for an easy introduction to bioinformatics concepts."
SHORT BOOK REVIEWS
"The book is self-contained and even includes a few pieces from calculus. The first four chapters are a solid introduction to basic probability theory, stochastic processes and statistics. The material is well seasoned with examples and problems related to genetics. Starting with chapter 6, the authors focus their efforts on modeling and DNA and protein sequences. ... The book is a very substantial and highly professional contribution to bioinformatics and applied statistics."
MATHEMATICAL REVIEWS
"This well-written textbook gives a survey of statistical, probabilistic and optimization methods that are used in bioinformatics. Without giving too many theoretical details, the book explains clearly how statistical and probabilistic techniques can be used to address bioinformatical problems...This book should be of interest both to graduate students and to trained statisticians, who want to learn more about the role of statistics in this fast growing field of application."
STATISTICAL METHODS IN MEDICAL RESEARCH
"This book provides an excellent survey of statistical analyses of biological sequence data and brief treatments of other areas of bioinformatics...The explanations and derivations of difficult ideas are usually clear. Frequent examples of bioinformatics applications help to maintain interest and to elucidate the statistical concepts presented. Without being excessively mathematical, the authors succeed in accurately presenting the assumptions and limitations of the statistical methods...This book describes and impressive breadth of applications including methods of sequencing, modeling searching, aligning and comparing DNA and protein sequences...this book I strongly recommended for an overview of statistical sequence analyses and for use in an advanced class in bioinformatics."
