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RRHGE: A Novel Approach to Classify the Estrogen Receptor Based Breast Cancer Subtypes
Joint Authors
Saini, Ashish
Hou, Jingyu
Zhou, Wanlei
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-01-19
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Background.
Breast cancer is the most common type of cancer among females with a high mortality rate.
It is essential to classify the estrogen receptor based breast cancer subtypes into correct subclasses, so that the right treatments can be applied to lower the mortality rate.
Using gene signatures derived from gene interaction networks to classify breast cancers has proven to be more reproducible and can achieve higher classification performance.
However, the interactions in the gene interaction network usually contain many false-positive interactions that do not have any biological meanings.
Therefore, it is a challenge to incorporate the reliability assessment of interactions when deriving gene signatures from gene interaction networks.
How to effectively extract gene signatures from available resources is critical to the success of cancer classification.
Methods.
We propose a novel method to measure and extract the reliable (biologically true or valid) interactions from gene interaction networks and incorporate the extracted reliable gene interactions into our proposed RRHGE algorithm to identify significant gene signatures from microarray gene expression data for classifying ER+ and ER− breast cancer samples.
Results.
The evaluation on real breast cancer samples showed that our RRHGE algorithm achieved higher classification accuracy than the existing approaches.
American Psychological Association (APA)
Saini, Ashish& Hou, Jingyu& Zhou, Wanlei. 2014. RRHGE: A Novel Approach to Classify the Estrogen Receptor Based Breast Cancer Subtypes. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1049330
Modern Language Association (MLA)
Saini, Ashish…[et al.]. RRHGE: A Novel Approach to Classify the Estrogen Receptor Based Breast Cancer Subtypes. The Scientific World Journal No. 2014 (2014), pp.1-13.
https://search.emarefa.net/detail/BIM-1049330
American Medical Association (AMA)
Saini, Ashish& Hou, Jingyu& Zhou, Wanlei. RRHGE: A Novel Approach to Classify the Estrogen Receptor Based Breast Cancer Subtypes. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1049330
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1049330