The importance of gene-centring microarray data

The Lancet Oncology

Volumn 11, Issue 8, 2010, Pages 719-720

  Sørlie, Therese ^a   Borgan, Eldrid ^a,c   Myhre, Simen ^a,c   Vollan, Hans Kristian ^a,c,d   Russnes, Hege ^a,c   Zhao, Xi ^a,c   Nilsen, Gro ^a   Lingjærde, Ole Christian ^b   Børresen Dale, Anne Lise ^a,c   Rødland, Einar ^a,b  

^a OSLO UNIVERSITY HOSPITAL   (Norway)

^b UNIVERSITY OF OSLO   (Norway)

^c UNIVERSITY OF OSLO   (Norway)

^d ULLEVÅL UNIVERSITY HOSPITAL   (Norway)

Author keywords

[No Author keywords available]

Indexed keywords

EPIDERMAL GROWTH FACTOR RECEPTOR 2;

ALGORITHM; ANALYTIC METHOD; BREAST CANCER; GENE EXPRESSION; GENETIC ANALYSIS; GENETIC ASSOCIATION; GENETIC DATABASE; GENETIC VARIABILITY; LETTER; PREDICTION; PRIORITY JOURNAL; PROTEIN MICROARRAY;

EID: 77955244785     PISSN: 14702045     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1470-2045(10)70174-1     Document Type: Letter

References (7)

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3. Sørlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 2001, 98:10869-10874.
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5. Lusa L, McShane LM, Reid JF, et al. Challenges in projecting clustering results across gene expression profiling datasets. J Natl Cancer Inst 2007, 99:1715-1723.
6. Hu Z, Fan C, Oh DS, et al. The molecular portraits of breast cancer are conserved across microarray platforms. BMC Genomics 2006, 7:96.
7. Parker JS, Mullins M, Cheang MC, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 2009, 27:1160-1167.