This is a protein complex prediction model based on hypergraph representation learning. HyperGraphComplex integrates high-order topological information from the protein-protein interaction (PPI) network and protein sequence features by simultaneously training the encoder and decoder using the HyperGraphVariational Autoencoder (HGVAE). This process generates latent feature vectors for protein complexes. Subsequently, a deep neural network (DNN) is employed to classify candidate protein sets.
All dependencies are included environment.yml in the method folder.
You could install all dependencies with conda:
conda env create -f environment.ymlTraning HyperGraphComplex base on Mann PPI . Enter the method folder：
python main.pyPredicting protein complex by HyperGraphComplex
python Predicting_protein_complex.py