1. Y Chen, E R Dougherty, M
L Bittner (2001),
"Ratio-based decisions
and the quantitative analysis of cDNA microarray images",
Journal of Biomedical
Optics, 2(4):364-374.
2. Cheng Li and Wing Hung
Wong (2001)
Model-based analysis of
oligonucleotide arrays: model validation, design issues and standard error
application,
Genome Biology 2(8): research0032.1-0032.11 (Abstract)
3. Cheng Li, Wing Hung Wong
(2001),
Model-based analysis of
oligonucleotide arrays: expression index computation and outlier detection.
Proceedings of the National
Academy of Sciences, 98:31-36.
4. Sandrine Dudoit, Yee Hwa
Yang, Matthew J Callow, Terry Speed,
preprint #578 (Statistics
Dept, UC Berkeley, Aug 2000).
5. O Ermolaeva, M Rastogi,
KD Pruitt, GD Schuler, ML Bittner, Y Chen, R Simon, P Meltzer, JM Trent, MS
Boguski (1998),
"Data management and
analysis for gene expression arrays",
Nature Genetics,
20(1):19-23.
6. EE Schadt, C Li, C Su, WH
Wong (2000),
"Analyzing
high-density oligonucleotide gene expression array data",
Journal of Cellular
Biochemistry, 80(2):192-202.
7. Yee Hwa Yang, Sandrine
Dudoit, Percy Luu, Terry Speed,
"Normalization
for cDNA microarray data",
preprint #589 (Statistics
Dept, UC Berkeley, Jan 2001).
8. M Kathleen Kerr, Gary A
Churchill (2001),
"Statistical design and
the analysis of gene expression microarrays, ",
Genetical Research, in
press.
9. V G Tusher, R Tibshirani,
G Chu (2001),
Significance analysis of
microarrays applied to the ionizing radiation response,
Proceedings of the National
Academy of Sciences, 98(9):5116-5121.
1. K. Y. Yeung and W. L. Ruzzo
Principal
component analysis for clustering gene expression data
Bioinformatics
2001 17: 763-774.
2. K. Y. Yeung, D. R. Haynor, and W. L. Ruzzo
Validating
clustering for gene expression data
Bioinformatics
2001 17: 309-318.
3. Interpreting
Gene Expression with Self-Organizing Maps: Methods and Application to
Hematopoeitic Differentiation Pablo Tamayo, Donna Slonim, Jill Mesirov,
Qing Zhu, Ethan Dmitrovsky, Eric S. Lander and Todd R. Golub
Published
version: Tamayo et al., PNAS 96:2907-2912, 1999
Preprint
version (MS Word 97, 2.5Mb): SOM_paper.rtf
4. Heping Zhang, Chang-Yung Yu, Burton Singer, Momiao Xiong
(2001),
"Recursive
partitioning for tumor classification with gene expression microarray
data",
Proceedings
of the National Academy of Sciences, 98(12):6730-6735.
5. TR
Golub, DK Slonim, P Tamayo, C Huard, M Caasenbeek, JP Mesirov, H Coller, ML
Loh, JR Downing, MA Caligiuri, CD Bloomfield, ES Lander (1999),
Science,
286:531-537.
Related
technical report (postscript): Class Prediction and Discovery using Gene
Expression Data.
The
published version of this report appeared in the Proceedings of the fourth annual
international conference on computational molecular biology April 8 - 11, 2000,
Tokyo Japan. RECOMB 2000, p263-272, 2000 .
6. Breiman, L. (1996a). Bagging predictors. Machine Learning
26(2), 123-140
7.
L. Breiman. Arcing
classifiers. Annals of Statistics 26:801-824, 1984
8.
Sandrine Dudoit, Jane
Fridlyand, Terry Speed,
"Comparison
of discrimination methods for the classification of tumors using gene expression
data",
preprint #576 (Statistics Dept, UC Berkeley, June 2000).
9. J Khan, J S Wei, M Ringnér, L H Saal, M Ladanyi, F Westermann, F Berthold, M Schwab, C R Antonescu, C Peterson & P S Meltzer (2001),
"Classification
and diagnostic prediction of cancers using gene expression profiling and
artificial neural networks",
Nature
Medicine, 7(6):673-679.
10. Breiman, L. (1999b)
Random Forests – Random Features, Technical Report 567,
Statistics
Dept. UCB, Berkeley