A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)

SSM-DTA: Breaking the Barriers of Data Scarcity in Drug-Target Affinity Prediction (Briefings in Bioinformatics 2023)

ExplainBind: Explainable Physicochemical Determinants of Protein–Ligand Binding via Non-Covalent Interactions

TAG-DTA: Binding Region-Guided Strategy to Predict Drug-Target Affinity Using Transformers

GENNDTI is a machine learning method that predicts drug-target interactions using a graph neural network enhanced by router nodes, effectively integrating biological properties of drugs and targets.

Drug-Target Interaction prediction using unifying of graph regularized nuclear norm with bilinear factorization

MVP de cribado virtual asistido por IA y docking molecular con biblioteca botanica de Ecuador y Amazonia.

An ensemble method implementation to predict drug–target interactions using embeddings and metadata

A weighted average ensemble method implementation to predict drug–target interactions

GenLoop — a closed generative drug-design loop on dtSFM; directed evolution of small molecules (Reddy 2026). Generate → encoder-rerank → AlphaFold-3 verify → LoRA-refine.

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