Orly Alter

TL;DR: In this article, singular value decomposition is used to transform genome-wide expression data from genes 3 arrays space to reduced diagonalized eigengenes 3 eigenarrays space.

TL;DR: Using singular value decomposition in transforming genome-wide expression data from genes x arrays space to reduced diagonalized "eigengenes" x "eigenarrays" space gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype.

TL;DR: These results suggest a new method for classification of soft-tissue tumours, which could improve on the method based on histological findings, and large numbers of uncharacterised genes contributed to distinctions between the tumours.

TL;DR: A comparative mathematical framework for two genome-scale expression data sets that formulates expression as superposition of the effects of regulatory programs, biological processes, and experimental artifacts common to both data sets by using generalized singular value decomposition is described.

TL;DR: The picture that emerges suggests that the conserved genes YKU70, MRE11, AIF1, and ZWF1, the processes of retrotransposition, apoptosis, and the oxidative pentose phosphate pathway that these genes are involved in, may play significant, yet previously unrecognized, roles in the differential effects of hydrogen peroxide and menadione on cell cycle progression.