May 18, 2024 · We propose a multi-label PPI prediction model referred to as CoMPPI (Co-training based Multi-Label prediction of Protein–Protein Interaction).

We propose a multi-label PPI prediction model referred to as CoMPPI (Co-training based Multi-Label prediction of Protein-Protein Interaction).

We present an innovative co-training based DL model for PPI type prediction. This model effectively captures both nominal and ordered features.

Jul 11, 2024 · Download Citation | On May 1, 2024, Tao Tang and others published Co-training based prediction of multi-label protein–protein interactions ...

Co-training based prediction of multi-label protein–protein interactions. https://doi.org/10.1016/j.compbiomed.2024.108623 ·. Journal: Computers in Biology ...

Dec 24, 2022 · In this brief review, we introduce currently available PPI databases and recent sequence-based methods for predicting PPIs.

May 19, 2022 · We use graph convolutional network (GCN) and graph attention network (GAT) to predict the interaction between proteins by utilizing protein's structural ...

May 9, 2024 · We proposed a novel graph neural network method called GNNGL-PPI for multi-category prediction of PPI based on global graphs and local subgraphs.

Oct 15, 2024 · We propose an anti-symmetric graph learning model, BaPPI, for the balanced prediction of PPIs and extrapolation of the involved patterns in PPI network.

Mar 14, 2024 · In this study, we propose a multi-source molecular network representation learning model (called MultiPPIs) to predict potential protein–protein interactions.