Inferring Update Sequences in Boolean Gene Regulatory Networks
Résumé
This paper employs mathematical programming and mixed integer linear programming techniques for solving a problem arising in the study of genetic
regulatory networks. More precisely, we solve the inverse problem consisting in the determination of the sequence of updates in the digraph representing
the gene regulatory network (GRN) of Arabidopsis thaliana in such a way that the generated gene activity is as close as possible to the observed data.
| Origine | Fichiers produits par l'(les) auteur(s) |
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