Supplemental material for O. Alter, P. O. Brown and D. Botstein, "Generalized Singular Value Decomposition for Comparative Analysis of Genome-Scale Expression Datasets of Two Different Organisms," Proceedings of the National Academy of Sciences (PNAS) USA 100 (6), pp. 3351–3356 (March 2003); doi: 10.1073/pnas.0530258100.
Feature: M. E. Kilmer and C. D. Moravitz Martin, "Decomposing a Tensor," SIAM News 37 (9), (November 2004).
Feature: J. Wixon and J. Ashurst, "Genome Informatics," Computational Functional Genomics 4 (5), pp. 509–514 (October 2003).
Abstract:
We describe a comparative mathematical framework for two genome-scale expression data sets. This framework formulates expression as superposition of the effects of regulatory programs, biological processes, and experimental artifacts common to both data sets, as well as those that are exclusive to one data set or the other, by using generalized singular value decomposition. This framework enables comparative reconstruction and classification of the genes and arrays of both data sets. We illustrate this framework with a comparison of yeast and human cell-cycle expression data sets.



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Yeast Expression Dataset and Classification Lists of Yeast Cell Cycle-Regulated Genes

Reproduced from Spellman et al.

Classification List of Yeast Pheromone Synchronization Response Genes

Gene Ontology (GO) annotations reproduced from Dwight et al.

Human Expression Dataset and Classification Lists of Human Cell Cycle-Regulated Genes

Reproduced from Whitfield et al.

Classification List of Human Synchronization Stress Response Genes

GO annotations reproduced from Sherlock et al.

Yeast and Human Arraylets Datasets