Identifying Hub Proteins and Their Essentiality from Protein-protein Interaction Network

Author

Bakar, S.A. ; Taheri, Javid ; Zomaya, Albert Y.

Author_Institution

Centre for Distrib. & High Performance Comput., Univ. of Sydney, Sydney, NSW, Australia

fYear

2011

fDate

24-26 Oct. 2011

Firstpage

266

Lastpage

269

Abstract

The study on protein-protein interactions is rapidly increasing; one of the most important findings of such study is the observation of hub proteins that play vital roles in all organisms. Identifying hub proteins may provide more information on essential proteins and lead to more efficient methods for their prediction. Here, we proposed a new network topological-based method for prediction of hub proteins in Saccharomyces cerevisiae (baker´s yeast). The method, HP³NN (Hub Protein Prediction using Probabilistic Neural Network), has successfully predicts the hub proteins with accuracy of 95% (sensitivity of 1.0 and specificity of 0.89).

Keywords

biology computing; microorganisms; molecular biophysics; neural nets; proteins; HP³NN; Saccharomyces cerevisiae; hub protein prediction; hub proteins; network topological-based method; probabilistic neural network; protein-protein interaction network; yeast; Bioinformatics; Neural networks; Neurons; Probabilistic logic; Proteins; Support vector machine classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Bioengineering (BIBE), 2011 IEEE 11th International Conference on

Conference_Location

Taichung

Print_ISBN

978-1-61284-975-1

Type

conf

DOI

10.1109/BIBE.2011.67

Filename

6092532