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 S�ren 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 S�ren 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. S�ren 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 [EMAIL PROTECTED]
