Proteomic mass spectra classification for biomarker discovery in prostate cancer ,employing pattern recognition techniques

dc.contributor.author	Μπουγιούκος, Παναγιώτης	el
dc.contributor.author	Κάβουρας, Διονύσης Α.	el
dc.contributor.author	Δασκαλάκης, Αντώνης	el
dc.contributor.author	Κωστόπουλος, Σπυρίδων	el
dc.contributor.author	Καλατζής, Ιωάννης	el
dc.date.accessioned	2015-05-14T17:23:01Z
dc.date.available	2015-05-14T17:23:01Z
dc.date.issued	2015-05-14
dc.identifier.uri	http://hdl.handle.net/11400/10407
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://www.bme.teiath.gr/medisp/pdfs/BOUGIOUKOS_2007_EpsMso_Proteomic%20Mass%20Spectra.pdf	en
dc.subject	Classification
dc.subject	Biomarker selection
dc.subject	Ταξινόμηση
dc.subject	Επιλογή βιοδείκτη
dc.title	Proteomic mass spectra classification for biomarker discovery in prostate cancer ,employing pattern recognition techniques	en
heal.type	conferenceItem
heal.classification	Medicine
heal.classification	Biomedical engineering
heal.classification	Ιατρική
heal.classification	Βιοϊατρική τεχνολογία
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh00006614
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85014237
heal.classificationURI	N/A-Ιατρική
heal.classificationURI	N/A-Βιοϊατρική τεχνολογία
heal.contributorName	Νικηφορίδης, Γεώργιος Σ.	el
heal.contributorName	Μπεζεριάνος, Αναστάσιος	el
heal.language	en
heal.access	free
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.	el
heal.publicationDate	2007
heal.bibliographicCitation	Bougioukos, P., Cavouras, D., Daskalakis, A., Kostopoulos, S., Kalatzis, I., et al. (2007). Proteomic mass spectra classification for biomarker discovery in prostate cancer ,employing pattern recognition techniques. In the 2nd International Conference on Experiments/ Process/ System Modelling/ Simulation/ Optimization (2nd IC-EpsMso). Greece, Athens, 4th-7th July 2007. Available from: http://www.bme.teiath.gr/medisp/pdfs/BOUGIOUKOS_2007_EpsMso_Proteomic%20Mass%20Spectra.pdf	en
heal.abstract	The purpose of the present study was the proposal of novel biomarkers in prostate cancer by analyzing mass spectrometry profiles. The latter were obtained from the National Cancer Institute Clinical Proteomics Database. The proposed method applied first a pre-processing pipeline of smoothing, automatic noise estimation, peak detection, and peak alignment, for improving the choice of information reach biomarkers and, second, a two level hierarchical tree structure classification scheme, where at each level a PNN classifier was optimally designed. At the first level, normal cases were discriminated by the PNN from cases with prostate cancer of PSA≥4 and, at the second level, distinction was made by the PNN between cancerous cases with 4≤PSA<10 and PSA>10. Maximum classification accuracies were 97.7% and 95.6% respectively. These high accuracies were achieved by a set of information reach biomarkers, which included the 2068.8m/z, 4675.6 m/z, and 5824.5 m/z values that have been associated with prostate cancer.	en
heal.fullTextAvailability	true
heal.conferenceName	International Conference on Experiments/ Process/ System Modelling/ Simulation/ Optimization	en
heal.conferenceItemType	full paper