Data from Curated Boolean Network
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https://figshare.com/articles/dataset/Data_from_Curated_Boolean_Network/26332933
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Data from Curated Boolean NetworkWe used BoolODE to generate simulated data from curated boolean models. BoolODE converts Boolean TF-gene regulations into ODEs, which more accurately simulate biological gene regulatory networks (GRNs) and single-cell gene expression dynamics. In this method, each network node has a 'gene' variable (mRNA level) and a 'protein' variable (TF level). We added noise to the curated data using the parameter s, and performed numerical integration with the Euler–Maruyama method. BoolODE effectively transforms a boolean model into an ODE model, simulating single-cell gene expression values.
BoolODE GitHub: https://murali-group.github.io/Beeline/BoolODE.html
Reference to the original paper: Pratapa, A., Jalihal, A.P., Law, J.N. et al. Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data. Nat Methods 17, 147–154 (2020). https://doi.org/10.1038/s41592-019-0690-6
创建时间：
2024-07-19
