Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods

Villmann T, Schleif F-M, Kostrzewa M, Walch A, Hammer B (2008)
Briefings in Bioinformatics 9(2): 129-143.

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Villmann T, Schleif F-M, Kostrzewa M, Walch A, Hammer B. Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods. Briefings in Bioinformatics. 2008;9(2):129-143.
Villmann, T., Schleif, F. - M., Kostrzewa, M., Walch, A., & Hammer, B. (2008). Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods. Briefings in Bioinformatics, 9(2), 129-143.
Villmann, T., Schleif, F. - M., Kostrzewa, M., Walch, A., and Hammer, B. (2008). Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods. Briefings in Bioinformatics 9, 129-143.
Villmann, T., et al., 2008. Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods. Briefings in Bioinformatics, 9(2), p 129-143.
T. Villmann, et al., “Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods”, Briefings in Bioinformatics, vol. 9, 2008, pp. 129-143.
Villmann, T., Schleif, F.-M., Kostrzewa, M., Walch, A., Hammer, B.: Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods. Briefings in Bioinformatics. 9, 129-143 (2008).
Villmann, Thomas, Schleif, Frank-Michael, Kostrzewa, Markus, Walch, Axel, and Hammer, Barbara. “Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods”. Briefings in Bioinformatics 9.2 (2008): 129-143.
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8 Citations in Europe PMC

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Divergence-based vector quantization.
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Cancer informatics by prototype networks in mass spectrometry.
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Walch A, Rauser S, Deininger SO, Hofler H., Histochem. Cell Biol. 130(3), 2008
PMID: 18618129

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