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This is an implementation of a gene regulatory network based on the work of Banzhaf and Nicolau. As the regulatory process is where most of the computation is tied up I implemented a c library to speed up this part of the code. There are also several datasets for testing the GRN.

License: GNU Lesser General Public License v3.0

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max_observed value

Thanks for the great code. Helped me a lot to code my version of GRNs. I found an issue with your code and although I'm not sure how this whole issue reporting thing works, I figured it might be helpful to share it here.

On line 170 of the grn.py, the same max_observed value has been calculated for both enh_matrix and inh_matrix which shouldn't be the case judging from the Banzhaf's GRN formula. I believe you did this code based on Nicolau's later paper which doesn't include separate formulas for both enhancers and inhibitors. So I believe your code should be changed to:

enh_matrix = enh_matrix - np.max(enh_matrix)
inh_matrix = inh_matrix - np.max(inh_matrix)

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