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  Kernel Methods for Predictive Sequence Analysis

Rätsch, G., & Ong, C. (2006). Kernel Methods for Predictive Sequence Analysis. Talk presented at German Conference on Bioinformatics (GCB 2006). Tübingen, Germany. 2006-09-19 - 2006-09-22.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0004-C9B4-E Version Permalink: http://hdl.handle.net/21.11116/0000-0004-C9B5-D
Genre: Talk

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GCB-2006-Ong.pdf (Any fulltext), 122KB
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GCB-2006-Ong.pdf
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 Creators:
Rätsch, G1, Author              
Ong, CS2, 3, Author              
Affiliations:
1Friedrich Miescher Laboratory, Max Planck Society, ou_2575692              
2Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
3Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: This tutorial is meant for a broad audience: Students, researchers, biologists and computer scientist interested in (a) an overview of general and efficient algorithms for statistical learning used in computational biology, (b) sequence kernels for the problems such as promoter or splice site detection. No specific knowledge will be required since the tutorial is self-contained and most fundamental concepts are introduced during the course.

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 Dates: 2006-09
 Publication Status: Published online
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Title: German Conference on Bioinformatics (GCB 2006)
Place of Event: Tübingen, Germany
Start-/End Date: 2006-09-19 - 2006-09-22
Invited: Yes

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