Title :
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
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;
Conference_Titel :
Advanced Information Networking and Applications, 2006. AINA 2006. 20th International Conference on
Print_ISBN :
0-7695-2466-4
DOI :
10.1109/AINA.2006.47
