Kernel Methods in Computational Biology A detailed overview of current research in kernel methods and their application to computational biology. Full description
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--Jun Liu, Professor of Statistics, Harvard University
--Junhyong Kim, Department of Biology, University of Pennsylvania
" This timely collection will be an asset to anyone working with microarray data, and those involved with computational biology more generally should be aware of it." --Jun Liu, Professor of Statistics, Harvard University
& quot; This timely collection will be an asset to anyone working with microarray data, and those involved with computational biology more generally should be aware of it.& quot; --Jun Liu, Professor of Statistics, Harvard University
"This unique collection admirably covers the topic of using kernel methods to study biological data, providing up-to-date treatment of work in the field."--Junhyong Kim, Department of Biology, University of Pennsylvania
"This timely collection will be an asset to anyone working with microarray data, and those involved with computational biology more generally should be aware of it."--Jun Liu, Professor of Statistics, Harvard University
Bernhard Schoelkopf is Director at the Max Planck Institute for Intelligent Systems in Tubingen, Germany. He is coauthor of Learning with Kernels (2002) and is a coeditor of Advances in Kernel Methods: Support Vector Learning (1998), Advances in Large-Margin Classifiers (2000), and Kernel Methods in Computational Biology (2004), all published by the MIT Press. Koji Tsuda is a Research Scientist at the Max Planck Institute and a Researcher at AIST Computational Biology Research Center, Tokyo. Jean-Philippe Vert is Researcher and Leader of the Bioinformatics Group at Ecole des Mines de Paris.
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