A graph-based model for predicting TF-target gene interactions and their types.
data/contains the necessary dataset files;main.pymain function for KGE-TGI.utils.pycontains functions for loading data, constructing heterogeneous graphs, and more.train.pycontains functions for traing model.model.pycontains the implementation of the KGE-TGI model and other related code.
This project is built on the following library versions:
- python==3.7
- numpy=1.21.5
- pytorch=1.8.1=py3.7_cuda10.2_cudnn7.6.5_0
- dgl-cu102==0.6.1
Useconda env create -f env.yaml to set up the environment.
Use the command python main.py to run the KGE-TGI model based on the provided data.
However, due to the combination of multiple biological network information, if you want to use your own data, data calibration and matching are currently required.
We will update the code as soon as possible to make it more user-friendly, allowing users to derive transcriptional regulatory relationships using their own data.