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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F11%3A00189932%21RIV12-MSM-21230___
rdf:type
n9:Vysledek skos:Concept
rdfs:seeAlso
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6112374
dcterms:description
This paper is devoted to analysis of voltammograms resulting from Brdicka reaction - these graphs are used for determination of content of metallothioneins (MT) in tissue samples most often. We describe our search for typical patterns in the considered curves motivated by our intention to identify their characteristic properties 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. This paper is devoted to analysis of voltammograms resulting from Brdicka reaction - these graphs are used for determination of content of metallothioneins (MT) in tissue samples most often. We describe our search for typical patterns in the considered curves motivated by our intention to identify their characteristic properties 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.
dcterms:title
Brdicka Curve - a New Source of BioMarkers Brdicka Curve - a New Source of BioMarkers
skos:prefLabel
Brdicka Curve - a New Source of BioMarkers Brdicka Curve - a New Source of BioMarkers
skos:notation
RIV/68407700:21230/11:00189932!RIV12-MSM-21230___
n9:predkladatel
n10:orjk%3A21230
n3:aktivita
n12:Z
n3:aktivity
Z(MSM6840770012)
n3:dodaniDat
n14:2012
n3:domaciTvurceVysledku
n7:9942904 Szabóová, Andrea n7:3799158 n7:5112605
n3:druhVysledku
n24:D
n3:duvernostUdaju
n16:S
n3:entitaPredkladatele
n5:predkladatel
n3:idSjednocenehoVysledku
188718
n3:idVysledku
RIV/68407700:21230/11:00189932
n3:jazykVysledku
n22:eng
n3:klicovaSlova
Electrochemical signal; Metallothionein; Classification
n3:klicoveSlovo
n23:Metallothionein n23:Electrochemical%20signal n23:Classification
n3:kontrolniKodProRIV
[252459F1C7D0]
n3:mistoKonaniAkce
Atlanta
n3:mistoVydani
Piscataway
n3:nazevZdroje
Bioinformatics and Biomedicine Workshops
n3:obor
n17:JC
n3:pocetDomacichTvurcuVysledku
4
n3:pocetTvurcuVysledku
6
n3:rokUplatneniVysledku
n14:2011
n3:tvurceVysledku
Adam, V. Štěpánková, Olga Szabóová, Andrea Kizek, R. Vysloužilová, Lenka Anýž, Jiří
n3:typAkce
n8:WRD
n3:zahajeniAkce
2011-11-12+01:00
n3:zamer
n15:MSM6840770012
s:numberOfPages
6
n21:doi
10.1109/BIBMW.2011.6112374
n20:hasPublisher
Institute of Electrical and Electronic Engineers
n19:isbn
978-1-4577-1611-9
n18:organizacniJednotka
21230