Large-scale reverse engineering by the Lasso
| dc.creator | Gustafsson, Mika | |
| dc.creator | Hornquist, Michael | |
| dc.creator | Lombardi, Anna | |
| dc.date | 2004-03-11 | |
| dc.date.accessioned | 2026-07-07T05:58:17Z | |
| dc.date.available | 2026-07-07T05:58:17Z | |
| dc.description | 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. | |
| dc.description | 4 pages, submitted for publication | |
| dc.identifier | https://arxiv.org/abs/q-bio/0403012 | |
| dc.identifier | http://arxiv.org/abs/q-bio/0403012 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/88301 | |
| dc.subject | Molecular Networks | |
| dc.title | Large-scale reverse engineering by the Lasso | |
| dc.type | text |