A mathematical re-analysis of microarray gene expression data reveals that the vast majority of expression patterns can be represented by just a few 'characteristic modes'.
In the July 18 [Proceedings of the National Academy of Sciences] Holter et al subject existing microarray gene expression data to a kind of spectral analysis (Proc. Natl. Acad. Sci. USA 2000, 97:8409-8414). This process of singular value decomposition (SVD) yields a set of "characteristic modes" that, when summed, reconstitute the entire expression pattern. But Holter et al find that just two or three of the modes are sufficient to describe the vast majority of the expression data. This shows that expression patterns are simple, usually undergoing a single "on to off" or "off to on" transition in response to a perturbation. Analysis of [cell cycle data] suggests that generally genes are not activated or repressed in large, discrete groups, as previously thought, but that cell cycle progression is a smooth function with roughly equal numbers of expression changes per unit time.
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