Segmentation Based Feature Selection on Classifying Proteomic Spectral Data

Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/79305

DC Field	Value	Language
dc.contributor	統計系
dc.creator	郭訓志	zh_TW
dc.creator	Kuo, Hsun-Chih;Yeh, Sheng-Tzung
dc.date	2015
dc.date.accessioned	2015-11-03T08:57:53Z	-
dc.date.available	2015-11-03T08:57:53Z	-
dc.date.issued	2015-11-03T08:57:53Z	-
dc.identifier.uri	http://nccur.lib.nccu.edu.tw/handle/140.119/79305	-
dc.description.abstract	Feature selection has been an important issue for classification of proteomic mass spectra data since researchers are often interested in identifying potentially important biomarkers. In this study, a segmentation approach is adopted to locate the potential biomarker regions from the possible m/z range. Illustration is through real prostate cancer proteomic mass spectra data.
dc.format.extent	194520 bytes	-
dc.format.mimetype	application/pdf	-
dc.relation	Lecture Notes in Computer Science,LNAI,112-119
dc.title	Segmentation Based Feature Selection on Classifying Proteomic Spectral Data
dc.type	conference	en
dc.identifier.doi	10.1007/978-3-319-19369-4_11
dc.doi.uri	http://dx.doi.org/10.1007/978-3-319-19369-4_11
item.fulltext	With Fulltext	-
item.openairecristype	http://purl.org/coar/resource_type/c_18cf	-
item.grantfulltext	restricted	-
item.cerifentitytype	Publications	-
item.openairetype	conference	-
Appears in Collections:	會議論文

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