Biomarker selection system, employing an iterative peak selection method, for identifying biomarkers related to prostate cancer

 
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2007 (EN)
Biomarker selection system, employing an iterative peak selection method, for identifying biomarkers related to prostate cancer (EN)

Μπουγιούκος, Παναγιώτης (EL)
Δασκαλάκης, Αντώνης (EL)
Κάβουρας, Διονύσης Α. (EL)
Καλατζής, Ιωάννης (EL)
Κωστόπουλος, Σπυρίδων (EL)

Νικηφορίδης, Γεώργιος Σ. (EL)
Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε. (EL)
Μπεζεριάνος, Αναστάσιος (EL)
Γεωργιάδης, Παντελής (EL)

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 MS-spectrum 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. (EN)

full paper
conferenceItem

Ταξινόμηση (EN)
Classification (EN)
Biomarker selection (EN)
Επιλογή βιοδείκτη (EN)

ΤΕΙ Αθήνας (EL)
Technological Educational Institute of Athens (EN)

International Conference Computer Analysis of Images and Patterns (EN)

English

2007

DOI 10.1007/978-3-540-74272-2_25

Springer Berlin Heidelberg (EN)



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