The authors of this text present the key machine learning approaches and apply them to the computational problems encountered in the analysis of biological data. The book is aimed at two types of researchers and students: firstly those biologists and biochemists who need to understand new data-driven algorithms, such as neural networks and hidden Markov models, in the context of biological sequences and their molecular structure and function; and secondly those with a primary background in physics, mathematics, statistics or computer science who need to know more about specific applications in molecular biology.
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This is a very good book, written with a high level of erudition and insight.
--Gustavo A. Stolovitzky, Physics TodayPierre Baldi is Professor of Information and Computer Science and of Biological Chemistry (College of Medicine) and Director of the Institute for Genomics and Bioinformatics at the University of California, Irvine. Soren Brunak is Professor and Director of the Center for Biological Sequence Analysis at the Technical University of Denmark.
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