Python library for attractor identification and control in Boolean networks
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Updated
May 23, 2024 - Jupyter Notebook
Python library for attractor identification and control in Boolean networks
Synthesis and Reprogramming of Most Permissive Boolean Networks
scBoolSeq: scRNA-Seq data binarisation and synthetic generation from Boolean dynamics
Distributed simulations and analysis of synchronous Boolean networks
In silico therapeutic target discovery using network attractors: avoiding pathological phenotypes
scRNA2BoNI - A general framework to infer Boolean networks from scRNAseq data.
The biologist's Boolean attractor landscape mapper, building Waddington landscapes from Boolean networks.
Notebooks demonstrating colomoto.minibn for computing dynamics of Boolean networks with various update modes
Enhancing Boolean networks with continuous logical operators and edge tuning: smoothing simulations
Executable paper and data demonstrating marker reprogramming of Boolean networks with BoNesis
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