forked from thmib/vertex-centrality-DILW
-
Notifications
You must be signed in to change notification settings - Fork 0
MIB-Lab/vertex-centrality-DILW
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
The original dataset is ds_filtered conducted by DisGeNet group. Constructing_Graphs.py generates two networks based on Formula 1 in the manuscript including disease network and gene networks. It reads the file “ds_filtered” as an input. The output for the disease network is disease_network_1. To preserve the multi-scale backbone of the weighted human disease network (WHDN) while removing less relevant and meaningful edges we use a multi-scale filtering method proposed by Serrano et al. [2009]. The result is the file “r_disease_network_1” and the giant component of the deducted network is given in “Giantr_disease_network_1”. Giantr_disease_network_1 is the file we apply the measures including DC, CC, BC, and W-DIL methods on it. In this file there are three columns that shows the given weight between two diseases. DIL_Method_W.py calculate the node importance scores calculated by DIL-W method. It reads file “Giantr_disease_network_1” as an input and gives scores to the nodes in the disease network. If you want to compare the DIL-W result with DC, CC, and BC the proper lines in the file must be uncommented.
About
No description, website, or topics provided.
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published
Languages
- Python 100.0%