VLBNs - Very Large Boolean Networks
<p>This archive contains instances of Boolean networks (in BoolNet format) generated from scale-free random network structure, on which has been applied the inhibitor-dominant rule to devise the logical functions.</p> <p>The generated networks range from 1,000 to 100,000 nodes, with in-degrees ranging up to 1400.</p> <p>Contents:</p> <ul> <li><a href="https://nbviewer.jupyter.org/urls/zenodo.org/record/3714876/files/Analysis.ipynb/%3Fdownload%3D1">Analysis.ipynb</a>: in/out-degree scatter plots of the generated networks</li> <li><a href="https://nbviewer.jupyter.org/urls/zenodo.org/record/3714876/files/Generation.ipynb/%3Fdownload%3D1">Generation.ipynb</a>: notebook used to generate the networks (requirs colomoto_jupyter python module)</li> <li>random-{N}-{id}.bnet: generated Boolean networks with N components</li> </ul>
ShareScore
40/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 4