Application of support vector machines to metabolomics experiments with limited replicates-Reference-Cited by-同舟云学术

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Application of support vector machines to metabolomics experiments with limited replicates

Published:2014-03-25 Issue:6 Volume:10 Page:1121-1128
ISSN:1573-3882
Container-title:Metabolomics
language:en
Short-container-title:Metabolomics

Author:

Heinemann Joshua,Mazurie Aurélien,Tokmina-Lukaszewska Monika,Beilman Greg J.,Bothner Brian

Publisher

Springer Science and Business Media LLC

Subject

Clinical Biochemistry,Biochemistry,Endocrinology, Diabetes and Metabolism

Link

http://link.springer.com/content/pdf/10.1007/s11306-014-0651-0.pdf

Reference22 articles.

1. Bertini, I., Calabro, A., De Carli, V., Luchinat, C., Nepi, S., Porfirio, B., et al. (2009). The metabonomic signature of celiac disease. Journal of Proteome Research, 8, 170–177.

2. Duan, K., Rajapakse, J. C., et al. (2005). Multiple SVM-RFE for gene selection in cancer classification with expression data. IEEE Transactions on Nanobioscience, 4, 228–234.

3. Guan, W., Zhou, M., Hampton, C. Y., Benigno, B. B., Walker, L. D., Gray, A., et al. (2009). Ovarian cancer detection from metabolomic liquid chromatography/mass spectrometry data by support vector machines. BMC Bioinformatics, 10, 259.

4. Guyon, I., Weston, J., Barnhill, S., et al. (2002). Gene selection for cancer classification using support vector machines. Machine Learning, 46, 389–422.

5. Hall, M., National, H., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., et al. (2010). The WEKA data mining software: An update. ACM SIGKDD Explorations Newsletter, 11(1), 10–18.

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