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• W1574273453 abstract "A biomarker selection system is proposed for identifying biomarkers related to prostate cancer. MS-spectra were obtained from the National Cancer Institute Clinical Proteomics Database. The system comprised two stages, a pre-processing stage, which is a sequence of MS-processing steps consisting of MSspectrum smoothing, novel iterative peak selection, peak alignment, and a classification stage employing the PNN classifier. The proposed iterative peak selection method was based on first applying local thresholding, for determining the MS-spectrum noise level, and second applying an iterative global threshold estimation algorithm, for selecting peaks at different intensity ranges. At each global threshold, an optimum sub-set of these peaks was used to design the PNN classifier for highest performance, in discriminating normal cases from cases with prostate cancer, and thus indicate the best m/z values. Among these values, the information rich biomarkers 1160.8, 2082.2, 3595.9, 4275.3, 5817.3, 7653.2, that have been associated with the prostate gland, are proposed for further investigation." @default.
• W1574273453 created "2016-06-24" @default.
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• W1574273453 date "2007-08-17" @default.
• W1574273453 modified "2023-09-26" @default.
• W1574273453 title "Biomarker Selection System, Employing an Iterative Peak Selection Method, for Identifying Biomarkers Related to Prostate Cancer" @default.
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• W1574273453 doi "https://doi.org/10.1007/978-3-540-74272-2_25" @default.
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