A parallel classification method for genomic and proteomic problems

Author

Guarracino, M.R. ; Cifarelli, C. ; Seref, O. ; Pardalos, P.M.

Author_Institution

High Performance Comput. & Networking Inst., Nat. Res. Council, Italy

Volume

2

fYear

2006

Abstract

Classification is one of the most widely used method in data mining with numerous applications in biomedicine. The scope and the resolution of data involved in many real life applications require very efficient implementations of classification methods, developed to run on parallel or distributed computational systems. In this study, a parallel implementation of an efficient algorithm that is based on regularized general eigenvalue classification is introduced. The proposed implementation is tested on a very large scale genomic data base and preliminary results regarding efficiency are presented.

Keywords

biology computing; data mining; eigenvalues and eigenfunctions; parallel processing; pattern classification; biomedicine; data mining; distributed computational system; eigenvalue classification; genomic-proteomic problem; large scale genomic data base; parallel classification method; Bioinformatics; Biomedical computing; Concurrent computing; Data mining; Distributed computing; Eigenvalues and eigenfunctions; Genomics; Large-scale systems; Proteomics; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Information Networking and Applications, 2006. AINA 2006. 20th International Conference on

ISSN

1550-445X

Print_ISBN

0-7695-2466-4

Type

conf

DOI

10.1109/AINA.2006.47

Filename

1620443