Sentence examples for random network generation from inspiring English sources
Imperial College's stochastic random network generation software developed by Idowu (2009) is used as a starting point in this research.
In addition, FANMOD allows the user to alter the random network generation process.
For this we used the 'switching permutation' method proposed by Ciriello et al. [ 17], which adopts a Markov chain Monte Carlo permutation strategy based on random network generation models.
To generate this null model, the authors make use of a permutation strategy based on a random network generation model referred to as the switching-algorithm (Milo et al., 2003).
To reconfirm our results reported in Table 1(g), we generated another set of 1000 random networks using an alternative method of random network generation – starting with the original network, over a large number of repetitions, two randomly chosen interactions are swapped.
However, they do not model RIGs in the same way we do: whereas we generate GEO-3D random networks using a generation process that does not require any knowledge about a real-world RIG other than its size, Bartoli et al. simply create randomized contact maps (i.e., RIGs).
Generation of random network is described in the methods section.
To provide support for the specificity of our coexpression network, we generated multiple random coexpression networks where gene assignments were randomized (Random Networks 1 3), as well as random networks where the gene expression levels were randomized (Random Networks 4 6).
For each network, 1000 random networks were generated conserving the degree sequence of the original network.
For each combination of network size and OLP, thirty to eighty populations were started from a random network and evolved until they either reached fitness of 0.99 or evolved for at least 10 million generations at a population size of 500.
To make it comparable, two network generation models are employed as null models: the scale-free model [ 14] and the ER random graph model [ 25]. 'Scale-free' networks exhibit power-law degree distributions.
