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

dc.contributor.author	Μπουγιούκος, Παναγιώτης	el
dc.contributor.author	Κάβουρας, Διονύσης Α.	el
dc.contributor.author	Δασκαλάκης, Αντώνης	el
dc.contributor.author	Καλατζής, Ιωάννης	el
dc.contributor.author	Κωστόπουλος, Σπυρίδων	el
dc.date.accessioned	2015-05-13T11:03:47Z
dc.date.available	2015-05-13T11:03:47Z
dc.date.issued	2015-05-13
dc.identifier.uri	http://hdl.handle.net/11400/10285
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://link.springer.com/chapter/10.1007/978-3-540-74272-2_25	en
dc.subject	Biomarker selection
dc.subject	Classification
dc.subject	Επιλογή βιοδείκτη
dc.subject	Ταξινόμηση
dc.title	Biomarker selection system, employing an iterative peak selection method, for identifying biomarkers related to prostate cancer	en
heal.type	conferenceItem
heal.generalDescription	Proceedings	en
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	Γεωργιάδης, Παντελής	el
heal.contributorName	Νικηφορίδης, Γεώργιος Σ.	el
heal.contributorName	Μπεζεριάνος, Αναστάσιος	el
heal.identifier.secondary	DOI 10.1007/978-3-540-74272-2_25
heal.language	en
heal.access	campus
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., Kalatzis, I., Kostopoulos, S., et al. (2007). Biomarker selection system, employing an iterative peak selection method, for identifying biomarkers related to prostate cancer. Proceedings of the 12th International Conference Computer Analysis of Images and Patterns. Vienna, Austria, 27th-29th August 2007. pp.197-204. Springer Berlin Heidelberg: 2007. Available from: http://link.springer.com/chapter/10.1007/978-3-540-74272-2_25	en
heal.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 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
heal.publisher	Springer Berlin Heidelberg	en
heal.fullTextAvailability	true
heal.conferenceName	International Conference Computer Analysis of Images and Patterns	en
heal.conferenceItemType	full paper