AEON.py: Python library for attractor analysis in asynchronous Boolean networks

• Authors: BENEŠ Nikola; BRIM Luboš; HUVAR Ondřej; PASTVA Samuel; ŠAFRÁNEK David; ŠMIJÁKOVÁ Eva
• Year of publication: 2022
• Type: Peer-reviewed scientific article
• Magazine / Source: BIOINFORMATICS
• MU Faculty or unit: Faculty of Informatics
• web: https://doi.org/10.1093/bioinformatics/btac624
• Doi: https://doi.org/10.1093/bioinformatics/btac624
• Keywords: Boolean Networks; Attractors; Software
• Description: AEON.py is a Python library for the analysis of the long-term behaviour in very large asynchronous Boolean networks. It provides significant computational improvements over the state-of-the-art methods for attractor detection. Furthermore, it admits the analysis of partially specified Boolean networks with uncertain update functions. It also includes techniques for identifying viable source-target control strategies and the assessment of their robustness with respect to parameter perturbations.

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