CNNC
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covolutional neural network based coexpression analysis
Hi is there a way to use many (10+) scRNA-seq datasets as as inputs. I realize one could simply try to integrate them into one dataset but I wanted to...
  
Is CNCC available or will be available in R? Thank you.
The rar file for pretrained models is not opening, it says no archives found, from where can I get the pretrained model?
Hi! I'm very interested in using your CNNC algorithm on one of my PhD. projects - it is great! I would like to test a couple of things before doing...
Hi, thanks for the great study. I just have a quick question about the transformation in get_xy_label_data_cnn_combine_from_database.py: HT = (log10(H / len(x_tf) + 10 ** -4) + 4) / 4...
Hi! In the paper, you mentioned: > KEGG contains 290 pathways, and Reactome contains 1,581 pathways. For both, we only select directed edges with either activation or inhibition edge types...
Hello, I got the result from predict_no_y.py, and the result .npy file was a Nx3 array (1,2,0 three labels in the trained model). And I have two quetions:  1....
Hello! I have a new problem: The get_xy_label_data_cnn_combine_from_database.py report an error when generate NEPDF data for the example sc-RNA seq h5 file `python CNNC/get_xy_label_data_cnn_combine_from_database.py \ None \ CNNC/data/sc_gene_list.txt \ CNNC/data/dendritic_gene_pairs_200.txt...
Hello! I want to predict some TF-target gene pairs with CNNC. However, I'm confused with the function of "data separation index list" file in section 7.2 and 8.2. The annotation...