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  Kernel Methods in Bioinformatics

Borgwardt, K. (2011). Kernel Methods in Bioinformatics. In H.-S. Lu, B. Schölkopf, & H. Zhao (Eds.), Handbook of Statistical Bioinformatics (pp. 317-334). Berlin, Germany: Springer.

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 Creators:
Borgwardt, K1, 2, Author           
Affiliations:
1Max Planck Institute for Developmental Biology, Max Planck Society, Max-Planck-Ring 5, 72076 Tübingen, DE, ou_2421691              
2Former Research Group Machines Learning Theory, Max Planck Institute for Intelligent Systems, Max Planck Society, DE, ou_1497665              

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 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.

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 Dates: 2011
 Publication Status: Issued
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 Rev. Type: -
 Identifiers: DOI: 10.1007/978-3-642-16345-6_15
BibTex Citekey: Borgwardt2011_2
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Title: Handbook of Statistical Bioinformatics
Source Genre: Book
 Creator(s):
Lu, HH-S1, Editor
Schölkopf, B1, Editor           
Zhao, H, Editor
Affiliations:
1 Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647            
Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 317 - 334 Identifier: ISBN: 978-3-642-16345-6

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Title: Springer Handbooks of Computational Statistics
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