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Open Access Highly Accessed Research article

Prediction of breast cancer prognosis using gene set statistics provides signature stability and biological context

Gad Abraham12, Adam Kowalczyk2, Sherene Loi34, Izhak Haviv567 and Justin Zobel12*

Author Affiliations

1 Department of Computer Science and Software Engineering, The University of Melbourne, Parkville 3010, VIC, Australia

2 NICTA Victoria Laboratory, The University of Melbourne, Parkville 3010, VIC, Australia

3 Department of Translational Research and Functional Genomics Unit, Jules Bordet Institute, Brussels, Belgium

4 Department of Medical Oncology, Peter MacCallum Cancer Centre, East Melbourne, VIC 3002, Australia

5 Metastasis Research Laboratory, Peter MacCallum Cancer Centre, East Melbourne, VIC 3002, Australia

6 The Blood and DNA Profiling Facility, Baker IDI Institute, Prahran, VIC 3004, Australia

7 Department of Biochemistry, School of Medicine, University of Melbourne, VIC 3010, Australia

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BMC Bioinformatics 2010, 11:277  doi:10.1186/1471-2105-11-277

Published: 25 May 2010

Additional files

Additional file 1:

supplementary. Further details on data preprocessing, methodology, and results including internal validation and comparisons of the centroid classifier with other classifiers.

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