T-FC Protein-Protein Interaction Predictor
Model Description
T-FC is a sequence-based protein–protein interaction (PPI) predictor that uses a Transformer backbone with a last-layer MLP. It produces a probability score for whether two proteins interact. This is an ablation of TUnA
Intended Use
- Rapid inference for candidate PPI scoring.
- These weights can be loaded in from the TUnA-R repository on Github.
Training Data
Trained on the Bernett dataset (https://academic.oup.com/bib/article/25/2/bbae076/7621029) composed of Human PPI interactions.
Model Architecture
Backbone: tuna.models._transformer.Transformer
protein_dim: 640hid_dim: 64ff_dim: 256n_layers: 1n_heads: 8dropout: 0.2llgp: Falseuse_spectral_norm: Falseout_targets: 1
Evaluation Results (Test Set)
- AUROC: 0.69
- MCC: 0.27
- Accuracy: 0.63
- AUPRC: 0.68
- Precision: 0.62
Citation
If you use this model, please cite:
- TUnA: https://academic.oup.com/bib/article/25/5/bbae359/7720609
- Bernett dataset: https://academic.oup.com/bib/article/25/2/bbae076/7621029
License
MIT
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