This paper describes the effects of perturbations, which simulatethe knock-out of single genes, one at a time, in random Boolean models ofgenetic networks (RBN). The analysis concentrates on the probability distributionof so-called avalanches (defined in the text) in gene expression. Thetopology of the random Boolean networks considered here is of the scale-freetype, with a power-law distribution of outgoing connectivities. The results forthese scale-free random Boolean networks (SFRBN) are compared with thoseof classical RBNs, which had been previously analyzed, and with experimentaldata on S. cerevisiae. It is shown that, while both models approximatethe main features of the distribution of experimental data, SFRBNs tend tooverestimate the number of large avalanches.
THE SIMULATION OF GENE KNOCK-OUT IN SCALE-FREE RANDOM BOOLEAN MODELS OF GENETIC NETWORKS / Serra, Roberto; Villani, Marco; Graudenzi, Alex; A., Colacci; S. A., Kauffman. - In: NETWORKS AND HETEROGENEOUS MEDIA. - ISSN 1556-1801. - STAMPA. - 3:2(2008), pp. 333-343. [10.3934/nhm.2008.3.333]
THE SIMULATION OF GENE KNOCK-OUT IN SCALE-FREE RANDOM BOOLEAN MODELS OF GENETIC NETWORKS
SERRA, Roberto;VILLANI, Marco;GRAUDENZI, Alex;
2008
Abstract
This paper describes the effects of perturbations, which simulatethe knock-out of single genes, one at a time, in random Boolean models ofgenetic networks (RBN). The analysis concentrates on the probability distributionof so-called avalanches (defined in the text) in gene expression. Thetopology of the random Boolean networks considered here is of the scale-freetype, with a power-law distribution of outgoing connectivities. The results forthese scale-free random Boolean networks (SFRBN) are compared with thoseof classical RBNs, which had been previously analyzed, and with experimentaldata on S. cerevisiae. It is shown that, while both models approximatethe main features of the distribution of experimental data, SFRBNs tend tooverestimate the number of large avalanches.Pubblicazioni consigliate
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