  Transcription networks, and other directed networks can be characterized by
some topological observables such as for example subgraph occurrence (network
motifs). In order to perform such kind of analysis, it is necessary to be able
to generate suitable randomized network ensembles. Typically, one considers
null networks with the same degree sequences of the original ones. The commonly
used algorithms sometimes have long convergence times, and sampling problems.
We present here an alternative, based on a variant of the importance sampling
Montecarlo developed by Chen et al. [1].
