BERT4DTI: BERT-based Model for Predicting Drug-Protein Interactions

arXiv:2609.33254 · cs.LG, cs.AI, cs.CL · Submitted 2026-09-27 · Read on arXiv

cs.LG, cs.AI, cs.CL

Submitted: 2026-09-27

Updated: 2026-09-27

Terminology

• AUC — 37× in this paper · explained in 2 episodes
• Benchmark — 16× in this paper · explained in 2 episodes
• Fine-Tuning — 14× in this paper · explained in 5 episodes
• Ablation — 5× in this paper · explained in 1 episode
• Adaptation — 4× in this paper · explained in 1 episode
• Transformer — 4× in this paper · explained in 2 episodes
• Calibration — 3× in this paper · explained in 7 episodes
• 1D CNN — 2× in this paper · explained in 2 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Attention Mechanism — 2× in this paper · explained in 3 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Computational Biology — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Knowledge Graph — 1× in this paper · explained in 7 episodes
• Knowledge graphs — 1× in this paper · explained in 2 episodes
• Late Fusion — 1× in this paper · explained in 2 episodes
• Parameter Efficiency — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Self-Supervised Learning — 1× in this paper · explained in 8 episodes

Sources

• ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks