-
1
-
-
0037076272
-
Diagnosis of multiple cancer types by shrunken centroids of gene expression
-
R. Tibshirani, T. Hastie, B. Narasimhan and G. Chu. Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc Natl Acad Sci U S A., 20:6567-6572, 2002.
-
(2002)
Proc Natl Acad Sci U S A
, vol.20
, pp. 6567-6572
-
-
Tibshirani, R.1
Hastie, T.2
Narasimhan, B.3
Chu, G.4
-
2
-
-
49649091962
-
Feature selection for predicting tumor metastases in microarray experiments using paired design
-
Q. Tan, M. Thomassen and T.A. Kruse. Feature selection for predicting tumor metastases in microarray experiments using paired design. Cancer Informatics, 2:133-138, 2007.
-
(2007)
Cancer Informatics
, vol.2
, pp. 133-138
-
-
Tan, Q.1
Thomassen, M.2
Kruse, T.A.3
-
3
-
-
12344267687
-
Gene expression signature with independent prognostic significance in epithelial ovarian cancer
-
D. Spentzos, D. A. Levine, M. F. Ramoni, M. Joseph, X. Gu, J. Boyd, T. A. Libermann and S. A. Cannistra. Gene expression signature with independent prognostic significance in epithelial ovarian cancer. J. Clin. Oncol., 22:4700-4710, 2004.
-
(2004)
J. Clin. Oncol.
, vol.22
, pp. 4700-4710
-
-
Spentzos, D.1
Levine, D.A.2
Ramoni, M.F.3
Joseph, M.4
Gu, X.5
Boyd, J.6
Libermann, T.A.7
Cannistra, S.A.8
-
4
-
-
33747360716
-
Predicting survival outcomes using subsets of significant genes in prognostic marker studies with microarrays
-
S. Matsui. Predicting survival outcomes using subsets of significant genes in prognostic marker studies with microarrays. BMC Bioinformatics, 7:156, 2006.
-
(2006)
BMC Bioinformatics
, vol.7
, pp. 156
-
-
Matsui, S.1
-
5
-
-
0035845501
-
Correspondence analysis applied to microarray data
-
K. Fellenberg, N. C. Hauser, B. Brors, A. Neutzner, J. D. Hoheisel and M. Vingron. Correspondence analysis applied to microarray data. Proc Natl Acad Sci U S A. 98: 10781-10786, 2001.
-
(2001)
Proc Natl Acad Sci U S A
, vol.98
, pp. 10781-10786
-
-
Fellenberg, K.1
Hauser, N.C.2
Brors, B.3
Neutzner, A.4
Hoheisel, J.D.5
Vingron, M.6
-
6
-
-
5644264936
-
Correspondence analysis of microarray time-course data in case-control design
-
Q. Tan, K. Brusgaard, T. A. Kruse, E. Oakeley, B. Hemmings, H. Beck- Nielsen, L. Hansen and M. Gaster. Correspondence analysis of microarray time-course data in case-control design, Journal of Biomedical Informatics, 37:358-365, 2004.
-
(2004)
Journal of Biomedical Informatics
, vol.37
, pp. 358-365
-
-
Tan, Q.1
Brusgaard, K.2
Kruse, T.A.3
Oakeley, E.4
Hemmings, B.5
Nielsen H.B.-6
Hansen, L.7
Gaster, M.8
-
7
-
-
0034602774
-
Knowledge-based analysis of microarray gene expression data by using support vector machines
-
M. P. Brown, W. N. Grundy, D. Lin, N. Cristianini, C. W. Sugnet, T. S. Furey, M. Ares and D. Haussler. Knowledge-based analysis of microarray gene expression data by using support vector machines. Proc Natl Acad Sci U S A. 97:262-267, 2000.
-
(2000)
Proc Natl Acad Sci U S A
, vol.97
, pp. 262-267
-
-
Brown, M.P.1
Grundy, W.N.2
Lin, D.3
Cristianini, N.4
Sugnet, C.W.5
Furey, T.S.6
Ares, M.7
Haussler, D.8
-
8
-
-
34547428435
-
A bootstrap correspondence analysis for factorial microarray experiments with replications
-
I. Mandoiu and A. Zelikovsky (eds), LNBI 4463, Springer-Verlag Berlin Heidelberg
-
Q. Tan, J. Dahlgaard, B. M. Abdallah, W. Vach, M. Kassem and T. A. Kruse. A bootstrap correspondence analysis for factorial microarray experiments with replications. In I. Mandoiu and A. Zelikovsky (eds), ISBRA 2007, LNBI 4463, pp.73-84. Springer-Verlag Berlin Heidelberg.
-
ISBRA 2007
, pp. 73-84
-
-
Tan, Q.1
Dahlgaard, J.2
Abdallah, B.M.3
Vach, W.4
Kassem, M.5
Kruse, T.A.6
-
9
-
-
85072725799
-
A hybrid approach for biomarker discovery from microarray gene expression data for cancer classification
-
Y. Peng, W. Li and Y. Liu. A hybrid approach for biomarker discovery from microarray gene expression data for cancer classification. Cancer Informatics. 2:301-311, 2006.
-
(2006)
Cancer Informatics
, vol.2
, pp. 301-311
-
-
Peng, Y.1
Li, W.2
Liu, Y.3
-
10
-
-
33749030973
-
Identifying genes that contribute most to good classification in microarrays
-
S. G. Baker and B. S. Kramer. Identifying genes that contribute most to good classification in microarrays. BMC Bioinformatics. 7:407, 2006.
-
(2006)
BMC Bioinformatics
, vol.7
, pp. 407
-
-
Baker, S.G.1
Kramer, B.S.2
-
11
-
-
33846827043
-
Prediction of metastasis from low-malignant breast cancer by gene expression profiling
-
M. Thomassen, Q. Tan, F. Eiriksdottir, M. Bak, S. Cold and T. A. Kruse. Prediction of metastasis from low-malignant breast cancer by gene expression profiling. International Journal of Cancer 120:1070-1075, 2007.
-
(2007)
International Journal of Cancer
, vol.120
, pp. 1070-1075
-
-
Thomassen, M.1
Tan, Q.2
Eiriksdottir, F.3
Bak, M.4
Cold, S.5
Kruse, T.A.6
-
12
-
-
13444282534
-
Outcome signature genes in breast cancer: Is there a unique set?
-
L. Ein-Dor, I. Kela, G. Getz, D. Givol and E. Domany. Outcome signature genes in breast cancer: is there a unique set? Bioinformatics. 21:171-178, 2005.
-
(2005)
Bioinformatics
, vol.21
, pp. 171-178
-
-
Ein-Dor, L.1
Kela, I.2
Getz, G.3
Givol, D.4
Domany, E.5
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