DocumentCode :
2764889
Title :
Brdicka curve — A new source of biomarkers
Author :
Vyslouzilova, Lenka ; Adam, Vojtech ; Szaboova, Andrea ; Stepankova, Olga ; Kizek, Rene ; Anyz, Jiri
Author_Institution :
Dept. of Cybern., CVUT, Prague, Czech Republic
fYear :
2011
fDate :
12-15 Nov. 2011
Firstpage :
193
Lastpage :
198
Abstract :
This paper is devoted to analysis of voltammograms resulting from Brdicka reaction - the graphs that are currently used for determination of content of metallothioneins (MT) in tissue samples most often. We describe our search for typical patterns in the considered curves that would make it possible to distinguish among voltammograms produced by samples taken from different body parts. We suggest a rather compact representation of information contained in the considered graphs that is based on Haar´s Simple Wavelet transformation. The resulting representation is successfully tested for classification of real data obtained from 8 rats and their 9 body parts. The preliminary experiments confirm that the suggested derived attributes of Brdicka curves seem to be good candidates for becoming numerical biomarkers exhibiting an important advantage: the process leading to their calculation can be fully automated.
Keywords :
Haar transforms; biochemistry; biological tissues; graphs; molecular biophysics; proteins; signal classification; signal processing; voltammetry (chemical analysis); wavelet transforms; Brdicka curve; Haar simple wavelet transformation; data classification; metallothioneins; numerical biomarkers; rats; tissue samples; voltammograms; Blood; Decision trees; Metals; Muscles; Proteins; Tumors; Wavelet transforms; Classification; Electrochemical signal; Metallothionein;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine Workshops (BIBMW), 2011 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4577-1612-6
Type :
conf
DOI :
10.1109/BIBMW.2011.6112374
Filename :
6112374
Link To Document :
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