License

This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program; if not, see http://www.gnu.org/licenses/.

MRLHGNN

MRLHGNN is effective tool for drug repositioning and we are thankful that Gu et al. have published part of their data which can be used directly.

Environment Requirement

torch version (GPU) == 2.0.1
CUDA version == 12.0
numpy == 1.34.3
matplotlib == 3.5.1
dgl-cu118 == 1.1.0
pandas == 1.5.3
scikit-learn == 1.2.2
torch-cluster == 1.6.1+pt20cu118
torch-scatter == 2.1.1+pt20cu118
torch-sparse == 0.6.17+pt20cu118
torch-spline-conv == 1.2.2+pt20cu118
torchaudio ==2.0.2
torchvision == 0.15.2

Model

load_data.py: Constructing heterogeneous graph.
SeHG.py: the core model proposed in the paper.

Compare_models

NTSIM (2017)
- Proposed in Predicting drug-disease associations based on the known association bipartite network, BIBM 2017.
BNNR (2019)
- Proposed in Drug repositioning based on bounded nuclear norm regularization, Bioinformatics 2019.
HGIMC (2020)
- Proposed in Heterogeneous graph inference with matrix completion for computational drug repositioning, Bioinformatics 2020.
NIMCGCN (2020)
- Proposed in Neural inductive matrix completion with graph convolutional networks for miRNA-disease association prediction, Bioinformatics 2020.
LAGCN (2021)
- Proposed in Predicting drug–disease associations through layer attention graph convolutional network, Briefings in Bioinformatics 2021.
DRHGCN (2021)
- Proposed in Drug repositioning based on the heterogeneous information fusion graph convolutional network, Briefings in Bioinformatics 2021.
DRWBNCF (2022)
- Proposed in A weighted bilinear neural collaborative filtering approach for drug repositioning, Briefings in Bioinformatics 2022.
REDDA (2022)
- Proposed in REDDA: Integrating multiple biological relations to heterogeneous graph neural network for drug-disease association prediction, Computers in Biology and Medicine 2022.
MilGNet (2022)
- Proposed in MilGNet: a multi-instance learning-based heterogeneous graph network for drug repositioning, BIBM 2022.

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