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

Saini, Ashish, Hou, Jingyu and Zhou, Wanlei 2013, Hub-based reliable gene expression algorithm to classify ER+ and ER- breast cancer subtypes, International journal of bioscience, biochemistry and bioinformatics, vol. 3, no. 1, pp. 20-26.

Attached Files
Name Description MIMEType Size Downloads

Title Hub-based reliable gene expression algorithm to classify ER+ and ER- breast cancer subtypes
Author(s) Saini, Ashish
Hou, Jingyu
Zhou, Wanlei
Journal name International journal of bioscience, biochemistry and bioinformatics
Volume number 3
Issue number 1
Start page 20
End page 26
Total pages 7
Publisher International Association of Computer Science and Information Technology Press
Place of publication Singapore
Publication date 2013
ISSN 2010-3638
Keyword(s) breast cancer diagnosis
estrogen-receptor
gene signature
hub-gene
Summary 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.
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
080299 Computation Theory and Mathematics not elsewhere classified
Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture)
HERDC Research category C1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30055336

Document type: Journal Article
Collection: School of Information Technology
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Access Statistics: 41 Abstract Views, 3 File Downloads  -  Detailed Statistics
Created: Tue, 27 Aug 2013, 12:01:54 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.