Improved Immune Genetic Algorithm for Clustering Protein-Protein Interaction Network

Author

Ravaee, Hamid ; Masoudi-Nejad, Ali ; Omidi, Saeed ; Moeini, Ali

Author_Institution

Lab. of Syst. Biol. & Bioinf. (LBB), Univ. of Tehran, Tehran, Iran

fYear

2010

fDate

May 31 2010-June 3 2010

Firstpage

174

Lastpage

179

Abstract

Clustering protein-protein interaction network aims to find functional modules and protein complexes. There are many computational graph clustering methods that are used in this field, but few of them are intelligent computational methods. In this paper, we present a novel improved immune genetic algorithm to find dense subgraphs based on efficient vaccination method, variable-length antibody schema definition and new local and global mutations.

Keywords

bioinformatics; genetics; graph theory; molecular biophysics; pattern clustering; proteins; clustering; dense subgraphs; immune genetic algorithm; mutations; protein-protein interaction network; vaccination method; variable-length antibody schema; Biochemistry; Biological system modeling; Biomedical engineering; Circadian rhythm; Genetic algorithms; Mathematical model; Power system modeling; Proteins; Systems biology; USA Councils; Graph clustering; Immune Genetic Algorithm; Protein Complex; Protein-protein Interaction;

fLanguage

English

Publisher

ieee

Conference_Titel

BioInformatics and BioEngineering (BIBE), 2010 IEEE International Conference on

Conference_Location

Philadelphia, PA

Print_ISBN

978-1-4244-7494-3

Type

conf

DOI

10.1109/BIBE.2010.36

Filename

5521693