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- W1618156912 abstract "We perform a reverse engineering from the “extended Spellman data”, consisting of 6178 mRNA levels measured by microarrays at 73 instances in four time series during the cell cycle of the yeast Saccharomyces cerevisae. By assuming a linear model of the genetic regulatory network, and imposing an extra constraint (the Lasso), we obtain a unique inference of coupling parameters. These parameters are transfered into an adjacent matrix, which is analyzed with respect to topological properties and biological relevance. We find a very broad distribution of outdegrees in the network, compatible with earlier findings for biological systems and totally incompatible with a random graph, and also indications of modules in the network. Finally, we show there is an excess of genes coding for transcription factors among the genes of highest outdegrees, a fact which indicates that our approach has biological relevance." @default.
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- W1618156912 date "2004-03-11" @default.
- W1618156912 modified "2023-09-27" @default.
- W1618156912 title "Large-scale reverse engineering by the Lasso" @default.
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