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Embedding Multilayer Networks for Omics Data Integration

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.github/workflows
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BRANEnet_TF_target_pred
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BRANEnet_emb
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baseline_emb
baseline_emb
 
 
BRANEnet.ipynb
BRANEnet.ipynb
 
 
BRANEnet.py
BRANEnet.py
 
 
BRANet_Edgelist_R_w_3_d_128_Module_1
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BRANet_Edgelist_R_w_3_d_128_Module_2
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BRANet_Edgelist_R_w_3_d_128_Module_4
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BRANet_Edgelist_R_w_3_d_128_Module_5
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BRANet_Edgelist_R_w_3_d_128_Module_7
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BRANet_Edgelist_R_w_3_d_128_NetworFile.txt
BRANet_Edgelist_R_w_3_d_128_NetworFile.txt
 
 
DEG_statistical_test_results.txt
DEG_statistical_test_results.txt
 
 
EdgeList_R.gml
EdgeList_R.gml
 
 
EdgeList_R_largestcc.gml
EdgeList_R_largestcc.gml
 
 
ION_inference.py
ION_inference.py
 
 
README.md
README.md
 
 
TF_target_average_pred_scores
TF_target_average_pred_scores
 
 
TF_target_l2_pred_scores
TF_target_l2_pred_scores
 
 
TF_target_pred_scores
TF_target_pred_scores
 
 
annotation_file.txt
annotation_file.txt
 
 
biogrid_refnet.txt
biogrid_refnet.txt
 
 
functions.py
functions.py
 
 
mcc.pdf
mcc.pdf
 
 
network_reconstruction.py
network_reconstruction.py
 
 
node_labels_all.pickle
node_labels_all.pickle
 
 
pr_at_k.pdf
pr_at_k.pdf
 
 
predict_ppi.py
predict_ppi.py
 
 
split_test_train.py
split_test_train.py
 
 
string_file.txt
string_file.txt
 
 
tf_deg_sgd.txt
tf_deg_sgd.txt
 
 

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BRANEnet

Embedding Multilayer Networks for Omics Data Integration ION

To reproduce the results, please run BRANEnet.ipynb

To compute embedding for user input network, Please run following command.

multilayer_networkfile = multilayer/single layer network file in 'gml' or 'edgelist' format

T = widow size

d = embedding dimension

type = 'gml' or 'edgelist'

python BRANEnet.py --multilayer_networkfile network_file.gml --T 3 --d 128 --type 'gml'

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