TUnA Protein Protein Interaction Predictor Model Description TUnA is a sequence based protein–protein interaction (PPI) predictor that uses a Transformer backbone with a last layer Gaussian process (LLGP). It produces a probability score for whether two proteins interact. Intended Use Research use for PPI prediction and representation learning. Rapid inference for candidate PPI scoring. 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 : 640 hid dim : 64 ff dim : 256 n layers : 1 n heads : 8 dropout : 0.2 llgp : True use spectral norm : True out targets : 1 gp config : rff features : 4096 gp cov momentum : 1 gp ridge penalty : 1 likelihood : "binary logistic" Evaluation Results (Test Set) AUROC: 0.70 AUPRC: 0.68 Accuracy: 0.65 MCC: 0.294 Precision: 0.65 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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