Python library for attractor identification and control in Boolean networks
-
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
BANG is a Python package dedicated to analysis, simulation, and control of Boolean networks with the help of CUDA.
In silico therapeutic target discovery using network attractors: avoiding pathological phenotypes
The biologist's Boolean attractor landscape mapper, building Waddington landscapes from Boolean networks.
scRNA2BoNI - A general framework to infer Boolean networks from scRNAseq data.
Enhancing Boolean networks with continuous logical operators and edge tuning: smoothing simulations
Notebooks demonstrating colomoto.minibn for computing dynamics of Boolean networks with various update modes
BoNesisTools is a python package proposing bioinformatics tools for upstream and downstream analysis of BoNesis framework
Executable paper and data demonstrating marker reprogramming of Boolean networks with BoNesis
Add a description, image, and links to the boolean-networks topic page so that developers can more easily learn about it.
To associate your repository with the boolean-networks topic, visit your repo's landing page and select "manage topics."