Searching for protein classification features

Author

Smith, Scott F.

Author_Institution

Dept. of Electr. & Comput. Eng., Boise State Univ., ID

Volume

1

fYear

2005

fDate

5-5 Sept. 2005

Firstpage

648

Abstract

A genetic algorithm is used to search for a set of classification features for a protein superfamily which is as unique as possible to the superfamily. These features may then be used for very fast classification of a query sequence into a protein superfamily. The features are based on windows onto modified consensus sequences of multiple aligned members of a training set for the protein superfamily. The efficacy of the method is demonstrated using receiver operating characteristic (ROC) values and the performance of resulting algorithm is compared with other database search algorithms

Keywords

biology computing; genetic algorithms; pattern classification; proteins; query processing; search problems; sequences; database search algorithm; genetic algorithm; modified consensus sequences; multiple aligned members; protein classification features; protein superfamily; query sequence classification; receiver operating characteristic; Classification algorithms; Data analysis; Evolutionary computation; Frequency; Genetic algorithms; Protein engineering; Sensitivity and specificity; Spatial databases; Web server;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2005. The 2005 IEEE Congress on

Conference_Location

Edinburgh, Scotland

Print_ISBN

0-7803-9363-5

Type

conf

DOI

10.1109/CEC.2005.1554744

Filename

1554744