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PMID: 14990457 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. Research Support, U.S. Gov't, P.H.S.

Support vector machine classification on the web.

Bioinformatics (Oxford, England) ·Vol. 20 ·No. 4 ·2004-03-01 ·Pages 586-7

Pavlidis P, Wapinski I, Noble WS

Abstract

The support vector machine (SVM) learning algorithm has been widely applied in bioinformatics. We have developed a simple web interface to our implementation of the SVM algorithm, called Gist. This interface allows novice or occasional users to apply a sophisticated machine learning algorithm easily to their data. More advanced users can download the software and source code for local installation. The availability of these tools will permit more widespread application of this powerful learning algorithm in bioinformatics.

MeSH Terms
Algorithms Artificial Intelligence Cluster Analysis Computing Methodologies Information Storage and Retrieval/methods Internet Pattern Recognition, Automated Software
Authors & Affiliations
3 authors, click to expand affiliations / ORCID
Pavlidis Paul
Columbia Genome Center and Department of Biomedical Informatics, Columbia University, 1150 St Nicholas Avenue, New York, NY 10032, USA. [email protected]
Wapinski Ilan
Noble William Stafford
Article Info
Journal
Bioinformatics (Oxford, England)
Abbr.
Bioinformatics
ISSN
1367-4803
Published
2004-03-01
Epub
2004-00-22
Pages
586-7
Language
English
Region
England
NLM ID
9808944
Subset
IM
Grants
NCRR NIH HHS · P41 RR08605 · United States
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