Machine Learning for Drug-Target Interaction Prediction

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Identify potential drug candidates within a high-quality compound search space

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Drug-Target Interaction Prediction Based on Gaussian Interaction Profile and Information Entropy

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Drug Prediction in Healthcare Using Big Data and Machine Learning

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A Methodology for the Prediction of Drug Target Interaction Using CDK Descriptors

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Drug-Target Interaction Prediction via an Ensemble of Weighted Nearest Neighbors with Interaction RecoveryPreprint

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Computational Approaches for Target Inference

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Machine Learning in Drug Discovery

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LINGO Profiles Fingerprint and Association Rule Mining for drug-target interaction prediction

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Computational Tools and Software in Drug Discovery

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DLMM-DTI: Deep Learning-Based Mamba Model for Drug-Target Interaction Binary Classification Prediction

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M 3 ST-DTI: A Multi-Task Learning Model for Drug-Target Interactions Based on Multi-Modal Features and Multi-Stage Alignment

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Drug - Drug Interaction Prediction System Using Machine Learning Algorithms

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Beyond the brain barrier: Hybrid nanoparticles orchestrating intelligent neuro-theranostics.

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Drugs with SMILES Similar to Coxibs

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Deep Neural Networks Predict Inhibitors ofSchistosoma MansoniThioredoxin Glutathione Reductase (SmTGR)

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Investigating the Use of Ensemble Learning for Drug Target Affinity Model

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Concentration-Dependent bidirectional regulation of adenosine receptor A1 explored through machine learning

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An Enhanced Computational Approach Using Multi-kernel Positive Unlabeled Learning for Predicting Drug-target Interactions

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Ant Colony-Based Sequential Hybrid Sampling Method for Handling the Imbalanced Data Problem in Drug-Target Interaction Prediction

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MuFAl: A Universal Drug-Target Interaction Prediction Framework

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MKDTI: Predicting Drug-Target Interactions via Multiple Kernel Fusion on Graph Attention Network

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LINGOBLM: using LINGO kernel in Bipartite Local Model

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Drug-Target Interaction Identification via Dual-Graph Regularized Robust PCA in Heterogeneous Networks

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A Critical Review On Predicting Drug-Drug Reactions Using Machine Learning Techniques

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Deep Learning Advancements in Target Delivery

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Unleashing Black Sea Cucumber's Potential: Identifying Anti-Cancer Compounds Through In Silico Drug DiscoveryPreprint

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Protocol for: A Simple, Accessible, Literature-based Drug Repurposing PipelinePreprint

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Deep Learning-Based i-EEG Classification with Convolutional Neural Networks for Drug-Target Interaction PredictionPreprint

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A Recommendation Perspective for Modeling Drug-Target Interaction Predictions Using Network-Based Approaches

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Chaotic Modified Binary Grey Wolf Optimizer Feature Selection method for Drug-Target interaction prediction Based on drug-protein Features

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Bio-inspired algorithm-based hyperparameter tuning for drug-target binding affinity prediction in healthcare

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A Hybrid ROS-SVM Model for Detecting Target Multiple Drug Types

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Link Prediction in Stagewise Graphs

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Boosting Federated Multitask Learning: Transfer Effects in Cross-Domain Drug-Target Interaction Prediction

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An Empirical Study to Analyse The Effect of Bagging and Feature Subspacing on The Performance of A Custom Ensemble Algorithm for Predicting Drug Protein Interactions

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Additional file 1 of Drug-target interaction prediction based on spatial consistency constraint and graph convolutional autoencoder

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Fast Bipartite Forests for Semi-supervised Interaction Prediction

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Artificial Intelligence: From Drug Discovery to Clinical Pharmacology

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On bipartite decision forests

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Genome Sequence Analysis and Drug-Target Interaction Prediction Using Deep Learning

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Triagem in silico de compostos com atividade ansiolítica encontrados na espécie Magnolia obovata

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Enhancing drug-target interaction predictions in context of neurodegenerative diseases using bidirectional long short-term memory in male Swiss albino mice pharmaco-EEG analysis

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Feature Extraction of Drug–Target Interactions Usingmodified Transformer Binding Phase

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The Influence of Artificial Intelligence in Drug Discovery and Development

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Enteric Protozoan Parasite Detection System: Linking to Neurodegenerative Diseases via the Gut-Brain Axis

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Quantum Machine Learning for Drug Discovery: A Systematic Review

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Advanced Biologics and Smart Delivery Systems for Cardiovascular Diseases: A Comprehensive Review

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DTIP-WINDGRU a novel drug-target interaction prediction with wind-enhanced gated recurrent unit

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Integrating artificial intelligence with precision medicine: a synergistic approach

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273 Explainable AI approaches in drug classification from biomarkers of epileptic seizure

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Discordance in Drug–Drug Interaction Alerts for Antidotes: Comparative Analysis of Electronic Databases and Interpretive Insights from AI Tools

Yaowaluk, T., Tangpanithandee, S., Techapichetvanich, P., & Khemawoot, P. (2025) · Drug Design Development and Therapy · doi:10.2147/dddt.s543827

HIN-MTDTI: Heterogeneous Information Networks for Multitask Drug–Target Interaction Prediction

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Enhancing Drug-Target Interaction Prediction: A Deep Learning Approach with Embedding-Based Representations

Abbasi, M., Váz, P., Silva, J. A., & Martins, P. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-08455-2_4

Enhancing drug repositioning: A multi-class ensemble model for drug-target interaction prediction with action type categorization

Khouzani, L. J., Sardari, S., Khouzani, S. J., Pérez‐Sánchez, H., & Ghasemi, F. (2025) · PLoS ONE · doi:10.1371/journal.pone.0333553

Additional file 1 of Explainable deep drug–target representations for binding affinity prediction

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Additional file 1 of Graph regularized non-negative matrix factorization with $$L_{2,1}$$ L 2 , 1 norm regularization terms for drug–target interactions prediction

Zhang, J., & Xie, M. (2024) · Figshare · doi:10.6084/m9.figshare.26622520

Additional file 2 of Graph regularized non-negative matrix factorization with $$L_{2,1}$$ L 2 , 1 norm regularization terms for drug–target interactions prediction

Zhang, J., & Xie, M. (2024) · Figshare · doi:10.6084/m9.figshare.26622523

AI Applications in Nuclear Medicine and Hybrid Imaging

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Domain adversarial gated bilinear attention networks for cross domain drug target interaction prediction

Lv, W., Zhang, Q., & Liu, L. (2026) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2026.153448

A novel graph neural network approach for predicting drug-target interactions

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Docking et Deep Learning : affinement de méthodologies in silico pour le développementde stratégies thérapeutiques innovantes

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Artificial Intelligence Towards Health Care and Its Role in Diagnostics and Treatment

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LapGAT: A Semi‐Supervised Learning Framework for Drug–Target Interaction Prediction

Song, L., Yuan, W., & Pei, X. (2026) · Molecular Informatics · doi:10.1002/minf.70028

Protein and ligand novelty in drug–target interaction prediction: a dual-encoder fusion strategy for more interpretable and generalizable modeling

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A multi-modal co-attention model for accurate drug-target interaction prediction

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Cheminformatic and Machine Learning based Approach for Predicting Drug Candidates

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Graph-based drug–target interaction modeling: from representation learning to output-driven drug discovery

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A Structure-Aware Multimodal Framework for Drug–Target Interaction Prediction via Heterogeneous Graph Learning

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PredictRx: AI based decision support tool for molecular screening for breast cancer drug recommendation

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KG-DFI: A Prediction of Drug–Food Interactions Based on Knowledge Graph Embedding

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Advancing cancer drug discovery through the integration of machine learning and high-throughput screening

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GADTI: A geometry-aware dual-tower framework for drug-target interaction prediction

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Dual-Modality Neural Network Integrating Sequence and Structural Information for Drug-Target Interaction Prediction

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The rise of agentic AI in drug discovery from static tools to autonomous virtual scientists

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