📩 Questions? Email us at
sybila@fi.muni.cz
🛠GitHub:
web-gui |
compute-engine
Beneš, N., Brim, L., Kadlecaj, J., Pastva, S., & Šafránek, D. (2020)
AEON: Attractor Bifurcation Analysis of Parametrised Boolean Networks.
In International Conference on Computer Aided Verification (CAV 2020), pp. 569–581.
AEON 2025 introduces functionality for control over Boolean networks. Users can now define control-relevant attributes and compute perturbations that guide the network toward a desired phenotype.
[tool] [manual]~ Older versions ~
Interactive tree editor for exploring bifurcation properties and attractor structures based on parameter space attributes. Includes variable stability analysis and witness generation.
Introduced a symbolic attractor detection algorithm. Massive scalability improvements, detailed static analysis for debugging, and enhancements to SBML compatibility.