DocumentCode
3002102
Title
Automatic Non-Structural Protien 1 recognition based on LDA classifier
Author
Twon Tawi, F.M. ; Lee, Khuan Y. ; Mansor, W. ; Radzol, A.R.M.
Author_Institution
Jabatan Kejuruteraan Elektrik, Politek. Seberang Perai, Perai, Malaysia
fYear
2013
fDate
Nov. 29 2013-Dec. 1 2013
Firstpage
340
Lastpage
343
Abstract
This paper discusses the possibilities of Non Structural Protein 1 (NS1) fingerprint can be classified from Raman spectra of saliva using Linear Discriminant Analysis (LDA). LDA is a supervised statistical method that can be used to classify two or more groups of data. In this research, Raman spectra of saliva and NS1-saliva mixture are obtained using Surface Enhanced Raman Spectroscopy (SERS) technique where gold coated slides (GS) are used as substrates. The NS1-saliva mixtures are prepared into different concentration of 10ppm, 50ppm and 100ppm. After applying simple LDA algorithm, the transformed data of saliva and NS1-saliva mixture are overlapping. However the overlapped data is reduced as the concentration of the mixture increase. It indicate that the algorithm is more suitable for samples with higher amount of NS1. Integration of LDA with other algorithm need to be considered for better classification.
Keywords
biological techniques; biology computing; fingerprint identification; gold; molecular biophysics; pattern classification; proteins; statistical analysis; surface enhanced Raman scattering; GS; LDA classifier; NS1 protein fingerprint classification; NS1 protein fingerprint recognition; NS1-saliva mixture; Raman spectra; SERS technique; automatic nonstructural protein 1 recognition; data classification; gold coated slides; linear discriminant analysis; supervised statistical method; surface enhanced Raman spectroscopy; Blood; Classification algorithms; Covariance matrices; Diseases; Gold; Proteins; Raman scattering; Linear Discriminant Linear Analysis (LDA); Non Structural Protein1 (NS1); SERS;
fLanguage
English
Publisher
ieee
Conference_Titel
Control System, Computing and Engineering (ICCSCE), 2013 IEEE International Conference on
Conference_Location
Mindeb
Print_ISBN
978-1-4799-1506-4
Type
conf
DOI
10.1109/ICCSCE.2013.6719986
Filename
6719986
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