An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence 
Analysis

Schweikert, G; Widmer, C; Schölkopf, B; Rätsch, G

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An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis

Schweikert, G., Widmer, C., Schölkopf, B., & Rätsch, G. (2009). An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis. In D. Koller, D. Schuurmans, Y. Bengio, & L. Bottou (Eds.), Advances in neural information processing systems 21 (pp. 1433-1440). Red Hook, NY, USA: Curran.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-C46B-8 Version Permalink: https://hdl.handle.net/21.11116/0000-000B-9C78-F

Genre: Conference Paper

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https://papers.nips.cc/paper/3407-an-empirical-analysis-of-domain-adaptation-algorithms-for-genomic-sequence-analysis.pdf (Publisher version) Open Access status unknown

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Creators:
Schweikert, G¹, Author
Widmer, C, Author
Schölkopf, B¹, Author
Rätsch, G, Author

Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795

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Abstract: We study the problem of domain transfer for a supervised classification task in mRNA splicing. We consider a number of recent domain transfer methods from machine learning, including some that are novel, and evaluate them on genomic
sequence data from model organisms of varying evolutionary distance. We find that in cases where the organisms are not closely related, the use of domain adaptation methods can help improve classification performance.

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Dates: Date issued: 2009-06

Publication Status: Issued

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Identifiers: BibTex Citekey: 5401

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Title: Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008)

Place of Event: Vancouver, BC, Canada

Start-/End Date: 2008-12-08 - 2008-12-10

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Title: Advances in neural information processing systems 21

Source Genre: Proceedings

Creator(s):
Koller, D, Editor
Schuurmans, D, Editor
Bengio, Y, Editor
Bottou, L, Editor

Affiliations:
-

Publ. Info: Red Hook, NY, USA : Curran

Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1433 - 1440 Identifier: ISBN: 978-1-60560-949-2