Using Eigenanalysis to Classify Proteins and Protein Motifs (CROSBI ID 583430)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Jeričević, Željko
engleski
Using Eigenanalysis to Classify Proteins and Protein Motifs
Eigenanalyis is a common name for linear algebra based multivariate analysis procedures like Principal Components Analysis (PCA), Correspondence Analysis (CA), Factor Analysis (FA), etc. The common idea in those methods is to compute eigenvalues and corresponding eigenvectors of a real symmetric matrix. The orthogonality of eigenvectors insures that the information contained in one vector is excluded from all other vectors and provides the basis for ordaining and filtering the information from original data set. We applied this methodology and freely accessible sequence information in open access biological data bases to classify proteins and their motifs in variety of situations like families of functionally related proteins, classifying functionally unknown proteins and/or finding new member of a known protein family. The performance of proposed methodology is illustrated on the analysis of nuclear receptor proteins family.
eigenanalysis; protein classification; protein motifs
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
Podaci o prilogu
297-299.
2011.
objavljeno
Podaci o matičnoj publikaciji
MIPRO, 2011 Proceedings of the 34th International Convention
Biljanović, Petar ; Skala, Karolj
Opatija: Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO
978-1-4577-0996-8
Podaci o skupu
MIPRO 2011
predavanje
23.05.2011-27.05.2011
Opatija, Hrvatska