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MVDA: a multi-view genomic data integration methodology

Published:2015-08-19 Issue:1 Volume:16 Page:
ISSN:1471-2105
Container-title:BMC Bioinformatics
language:en
Short-container-title:BMC Bioinformatics

Author:

Serra Angela,Fratello Michele,Fortino Vittorio,Raiconi Giancarlo,Tagliaferri Roberto,Greco Dario

Funder

Seventh Framework Programme

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

Link

http://link.springer.com/content/pdf/10.1186/s12859-015-0680-3.pdf

Reference38 articles.

1. Chang HY, Nuyten DS, Sneddon JB, Hastie T, Tibshirani R, Sørlie T, et al. Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival. Proc National Acad Sci U S A. 2005; 102(10):3738–43.

2. Huang E, Cheng SH, Dressman H, Pittman J, Tsou MH, Horng CF, et al. Gene expression predictors of breast cancer outcomes. The Lancet. 2003; 361(9369):1590–6.

3. West M, Blanchette C, Dressman H, Huang E, Ishida S, Spang R, et al. Predicting the clinical status of human breast cancer by using gene expression profiles. Proc National Acad Sci. 2001; 98(20):11462–7.

4. Sørlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc National Acad Sci. 2001; 98(19):10869–74.

5. Vang Nielsen K, Ejlertsen B, Møller S, Trøst Jørgensen J, Knoop A, Knudsen H, et al. The value of top2a gene copy number variation as a biomarker in breast cancer: Update of dbcg trial 89d. Acta Oncologica. 2008; 47(4):725–34.

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