I thought readers of the Uncertainty in AI List might be interested in this
book. For more information please visit http://mitpress.mit.edu/026202506X
Bioinformatics
The Machine Learning Approach
second edition
Pierre Baldi and Søren Brunak
An unprecedented wealth of data is being generated by genome sequencing
projects and other experimental efforts to determine the structure and
function of biological molecules. The demands and opportunities for
interpreting these data are expanding rapidly. Bioinformatics is the
development and application of computer methods for management, analysis,
interpretation, and prediction, as well as for the design of experiments.
Machine learning approaches (e.g., neural networks, hidden Markov models,
and belief networks) are ideally suited for areas where there is a lot of
data but little theory, which is the situation in molecular biology. The
goal in machine learning is to extract useful information from a body of
data by building good probabilistic models--and to automate the process as
much as possible.
In this book Pierre Baldi and Søren Brunak present the key machine learning
approaches and apply them to the computational problems encountered in the
analysis of biological data. The book is aimed both at biologists and
biochemists who need to understand new data-driven algorithms and at those
with a primary background in physics, mathematics, statistics, or computer
science who need to know more about applications in molecular biology.
This edition contains expanded coverage of probabilistic graphical models
and of the applications of neural networks, as well as a new chapter on
microarrays and gene expression. The entire text has been extensively revised.
Pierre Baldi is Professor and Director of the Institute for Genomics and
Bioinformatics in the Department of Information and Computer Science and in
the Department of Biological Chemistry in the College of Medicine at the
University of California, Irvine. Søren Brunak is Professor and Director of
the Center for Biological Sequence Analysis at the Biocentrum of the
Technical University of Denmark.
7 x 9, 400 pp., 72 illus.
cloth ISBN 0-262-02506-X
Adaptive Computation and Machine Learning series
A Bradford Book
Jud Wolfskill
Associate Publicist
MIT Press
5 Cambridge Center, 4th Floor
Cambridge, MA 02142
617.253.2079
617.253.1709 fax
wolfskil@mit.edu
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