Course Reading List for 3-4

Course Reading List For 3-4

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,

"Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments",

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.

Sections 5-8

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),

"Molecular classification of cancer: class discovery and class prediction by gene expression monitoring", 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