Classification of breast cancer patients using somatic mutation profiles and machine learning approaches-Reference-Cited by-同舟云学术

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Classification of breast cancer patients using somatic mutation profiles and machine learning approaches

Published:2016-08 Issue:S3 Volume:10 Page:
ISSN:1752-0509
Container-title:BMC Systems Biology
language:en
Short-container-title:BMC Syst Biol

Author:

Vural Suleyman,Wang Xiaosheng,Guda Chittibabu

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Modeling and Simulation,Structural Biology

Link

http://link.springer.com/content/pdf/10.1186/s12918-016-0306-z

Reference41 articles.

1. Elston C, Ellis I, Pinder S. Pathological prognostic factors in breast cancer. Crit Rev Oncol Hematol. 1999;31:209–23.

2. Perou C, Sørlie T, Eisen M. Molecular portraits of human breast tumours. Nature. 2000;533:747–52.

3. Sørlie T, Perou C. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci. 2001;98:10869–74.

4. Hu Z, Fan C, Oh DS, Marron JS, He X, Qaqish BF, Livasy C, Carey LA, Reynolds E, Dressler L, Nobel A, Parker J, Ewend MG, Sawyer LR, Wu J, Liu Y, Nanda R, Tretiakova M, Ruiz Orrico A, Dreher D, Palazzo JP, Perreard L, Nelson E, Mone M, Hansen H, Mullins M, Quackenbush JF, Ellis MJ, Olopade OI, Bernard PS,et al. The molecular portraits of breast tumors are conserved across microarray platforms. BMC Genomics. 2006;7:96.

5. Ali HR, Rueda OM, Chin S-F, Curtis C, Dunning MJ, Aparicio SA, Caldas C. Genome-driven integrated classification of breast cancer validated in over 7,500 samples. Genome Biol. 2014;15:431.

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