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Kernel Methods in Bioinformatics

  • Karsten M. BorgwardtEmail author
Chapter
Part of the Springer Handbooks of Computational Statistics book series (SHCS)

Abstract

Kernel methods have now witnessed more than a decade of increasing popularity in the bioinformatics community. In this article, we will compactly review this development, examining the areas in which kernel methods have contributed to computational biology and describing the reasons for their success.

Keywords

Support Vector Machine Kernel Method Prediction Task Multiple Kernel Learning Protein Function Prediction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.Machine Learning and Computational Biology Research GroupMax Planck Institute for Intelligent Systems and Max Planck Institute for Developmental Biology, TübingenTübingenGermany

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