Naslov
Using Eigenanalysis to Classify Proteins and Protein Motifs

Autori
Jeričević, Željko

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
MIPRO, 2011 Proceedings of the 34th International Convention / Biljanović, Petar ; Skala, Karolj - Opatija : Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2011, 297-299

ISBN
978-1-4577-0996-8

Skup
MIPRO 34th International Convention, GVS Section

Mjesto i datum
Opatija, Hrvatska, 23.05.2011. - 27.05.2011

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
eigenanalysis; protein classification
(eigenanalysis; protein classification; protein motifs)

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Biologija, Računarstvo

POVEZANOST RADA