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References

R: R Development Core Team (2008). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org

affy package for CEL files preprocessing: Gautier, L., Cope, L., Bolstad, B. M., and Irizarry, R. A. 2004. affy---analysis of Affymetrix GeneChip data at the probe level. Bioinformatics 20, 3 (Feb. 2004), 307-315

gcrma R package: Jean(ZHIJIN) Wu and Rafael Irizarry with contributions from James MacDonald Jeff Gentry (). gcrma: Background Adjustment Using Sequence Information. R package version 2.14.1.

limma package: Smyth, GK (2005). Limma: linear models for microarray data. In:  'Bioinformatics and Computational Biology Solutions using R and Bioconductor'. R. Gentleman, V. Carey, S. Dudoit, R. Irizarry, W.  Huber (eds), Springer, New York, pages 397-420.

edgeR package: Robinson MD, McCarthy DJ and Smyth GK (2010). edgeR: a Bioconductor

package for differential expression analysis of digital gene expression data. Bioinformatics 26,139-140.

Quantile normalization: Bolstad, B. M. Irizarry, R. A.  Astrand, M. and Speed, T. P.  A Comparison of Normalization Methods for High Density Oligonucleotide Array Data Based on Variance and Bias. Bioinformatics   19(2):185-193, 2003 

Non-linear baseline normalization: Schadt, E., C. Li, B. Eliss, and W. H. Wong. Feature extraction and normalization algorithms for high-density oligonucleotide gene expression array data.  J. Cell. Biochem. 84(S37),120–125, 2002

SAM (Significance Analysis of Microarray):

V. Tusher., R. Tibshirani., and G. Chu. Significance analysis of microarrays applied to the ionizing radiation response. PNAS, 98: 5116-5121, 2001

R. Tibshirani, G. Chu, T. Hastie and Balasubramanian Narasimhan (). samr: SAM: Significance Analysis of Microarrays. R package version 1.26. http://www-stat.stanford.edu/~tibs/SAM

K-Means clustering algorithm: Tavazoie, S., Hughes, J. D., Campbell, M. J., Cho, R. J., and Church, G. M. Systematic determination of genetic network architecture. Nat Genet, 22: 281-285, 1999

SOM clustering algorithm: Tamayo, P., Slonim, D., Mesirov, J., Zhu, Q., Kitareewan, S., Dmitrovsky, E., Lander, E. S., and Golub, T. R. Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. Proc Natl Acad Sci U S A, 96, 2907-2912, 1999

CLICK clustering algorithm: Sharan, R. and Shamir, R. CLICK: a clustering algorithm with applications to gene expression analysis. Proc Int Conf Intell Syst Mol Biol 8, 307-16, 2000

ISA Biclustering algorithm:   Bergmann, S., Ihmels, J., Barkai, N.
Iterative signature algorithm for the analysis of large-scale gene expression data. Phys Rev E Stat Nonlin Soft Matter Phys 2003 Mar; 67(3 Pt 1)

 

SAMBA biclustering algorithm: Tanay, A. Sharan, R. and Shamir, R. Discovering statistically significant biclusters in gene expression data. Bioinformatics, 18(1), 136-144, 2002

Matisse network grouping: Ulitsky, I. and Shamir, R. MATISSE: Identification of functional modules using network topology and high-throughput data. BMC Systems Biology, vol 1, No. 8 (2007)

Degas network grouping:

Ulitsky, I., Karp , R.M. and Shamir, R.

Detecting Disease-Specific Dysregulated Pathways Via Analysis of Clinical Expression Profiles
Proceedings of RECOMB 2008, pp. 347--359, LNBI 4955, Springer, Berlin, (2008).


Context Scores for miRNA enrichment analysis:  Grimson, A.,
Kai-How Farh, F. K Johnston, W., Garrett-Engele, F., P Lim, L., P Bartel, D. MicroRNA Targeting Specificity in Mammals: Determinants beyond Seed Pairing. Molecular Cell, 27:91-105 (2007)

PRIMA algorithm: Elkon, R., Linhart, C. Sharan, R. Samir, R. and Shiloh, Y. Genome-Wide In Silico Identification of Transcriptional Regulators Controlling the Cell Cycle in Human Cells. Genome Research, Vol. 13(5), pp. 773-780, 2003.

Spike software and DB: R. Elkon, R. Vesterman, N. Amit, I. Ulitsky, I. Zohar, M. Weisz, G. Mass, N. Orlev, G. Sternberg, R. Blekhman, J. Assa, Y. Shiloh and R.Shamir. SPIKE - a database, visualization and analysis tool of cellular signaling pathways. BMC Bioinformatics 2008, 9:11

Spike home page: http://www.cs.tau.ac.il/~spike/

Agglomerative algorithm for hierarchical clustering: Eisen, M. B., Spellman, P. T. et al. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci U S A 95(25), 14863-8, 1998

TF binding site profiles that were used to generate the supplied yeast TF fingerprint files: Harbison, C.T., D.B. Gordon, T.I. Lee, N.J. Rinaldi, K.D. Macisaac, T.W. Danford, N.M. Hannett, J.B. Tagne, D.B. Reynolds, J. Yoo, E.G. Jennings, J. Zeitlinger, D.K. Pokholok, M. Kellis, P.A. Rolfe, K.T. Takusagawa, E.S. Lander, D.K. Gifford, E. Fraenkel, and R.A. Young. Transcriptional regulatory code of a eukaryotic genome. Nature 431: 99-104, 2004

expressionData1.txt sample input file: Spellman, P. T., Sherlock, G., et al. Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol Biol Cell 9(12), 3273-97, 1998

Gene Set Enrichment Analysis: Aravind Subramanian, Pablo Tamayo, Vamsi K. Mootha, Sayan Mukherjee, Benjamin L. Ebert, Michael A. Gillette, Amanda Paulovich, Scott L. Pomeroy, Todd R. Golub, Eric S. Lander, and Jill P. Mesirov. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. PNAS vol. 102,   no. 43, 15545–15550, 2005

 


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