Current composite-feature classification methods do not outperform simple single-genes classifiers in breast cancer prognosis

Current composite-feature classification methods do not outperform simple single-genes classifiers in breast cancer prognosis

Integrating gene expression data with secondary data such as pathway or protein-protein interaction data has been proposed as a promising approach for improved outcome prediction of cancer patients. Methods employing this approach usually aggregate the expression of genes into new composite features...

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Bibliographic Details
Main Authors: Christine eStaiger, Sidney eCadot, Balázs eGyörffy, Lodewyk FA Wessels, Gunnar W Klau
Format: Article
Language:English
Published: Frontiers Media S.A. 2013-12-01
Series:Frontiers in Genetics
Subjects:
Classification
Software
breast cancer
networks
Evaluation
Feature Selection
Online Access:http://journal.frontiersin.org/Journal/10.3389/fgene.2013.00289/full

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