The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly.
From the reviews: "This book is a collection of chapters describing methods of statistical analysis of medical and biological data, with a focus on mathematical descriptions and implementing algorithms. ! It will be particularly useful for those who are interested in a better understanding of artificial neutral networks ! . Generally, it is a refreshing book for a statistician ! giving a good description of a wide variety of complex models." (Natalia Bochkina, Significance, Vol. 3 (3), 2006) "This book covers recent advances in the use of probabilistic models in computational molecular biology, bioinformatics and biomedicine. ! A self-contained chapter on statistical inference is included as well as a discussion of Bayesian networks as a common and unifying framework for probabilistic modeling. The book has been written for researchers and students in statistics, informatics, and biological sciences ! . Finally, an appendix explains the conventions and notation used throughout the book." (T. Postelnicu, Zentralblatt MATH, Vol. 1151, 2009)
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