Deakin University
Browse
saini-hubbasedreliable-2013.pdf (1.24 MB)

Hub-based reliable gene expression algorithm to classify ER+ and ER- breast cancer subtypes

Download (1.24 MB)
journal contribution
posted on 2013-01-01, 00:00 authored by A Saini, Jingyu HouJingyu Hou, Wanlei Zhou
Identifying gene signatures that are associatedwith the estrogen receptor based breast cancer samples is achallenging problem that has significant implications in breastcancer diagnosis and treatment. Various existing approaches foridentifying gene signatures have been developed but are not ableto achieve the satisfactory results because of their severallimitations. Subnetwork-based approaches have shown to be arobust classification method that uses interaction datasets suchas protein-protein interaction datasets. It has been reported thatthese interaction datasets contain many irrelevant interactionsthat have no biological meaning associated with them, and thusit is essential to filter out those interactions which can improvethe classification results. In this paper, we therefore, proposed ahub-based reliable gene expression algorithm (HRGE) thateffectively extracts the significant biologically-relevantinteractions and uses hub-gene topology to generate thesubnetwork based gene signatures for ER+ and ER- breastcancer subtypes. The proposed approach shows the superiorclassification accuracy amongst the other existing classifiers, inthe validation dataset.

History

Journal

International journal of bioscience, biochemistry and bioinformatics

Volume

3

Issue

1

Pagination

20 - 26

Publisher

International Association of Computer Science and Information Technology Press

Location

Singapore

ISSN

2010-3638

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Usage metrics

    Research Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC