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Profiled support vector machines for antisense oligonucleotide efficacy prediction.

Authors
  • Camps-Valls, Gustavo
  • Chalk, Alistair M
  • Serrano-López, Antonio J
  • Martín-Guerrero, José D
  • Sonnhammer, Erik L L
Type
Published Article
Journal
BMC Bioinformatics
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Sep 22, 2004
Volume
5
Pages
135–135
Identifiers
PMID: 15383156
Source
Medline
License
Unknown

Abstract

The SVM approach is well suited to the AO prediction problem, and yields a prediction accuracy superior to previous methods. The profiled SVM was found to perform better than the standard SVM, suggesting that it could lead to improvements in other prediction problems as well.

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