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Kernel Methods for Predictive Sequence Analysis

MPS-Authors
/persons/resource/persons84153

Rätsch,  G
Friedrich Miescher Laboratory, Max Planck Society;

/persons/resource/persons84118

Ong,  CS
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Fulltext (public)

GCB-2006-Ong.pdf
(Any fulltext), 122KB

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Citation

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.


Cite as: http://hdl.handle.net/21.11116/0000-0004-C9B4-E
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.