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selfRL: Two-Level Self-Supervised Transformer Representation Learning for Link Prediction of Heterogeneous Biomedical NetworksPreprint

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An Efficient Computational Method to Predict Drug-Target Interactions Utilizing Structural Perturbation Method

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Relational Topology-Based Heterogeneous Network Embedding for Predicting Drug-Target InteractionsPreprint

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A Meta-Path based Drug-Target Prediction Model with Collaborative Attention Mechanisms

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BGAT: A Multi Information Fusion Drug Repurposing Framework Based on Graph Convolutional Network

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TripletMultiDTI: Multimodal Representation Learning in Drug-Target Interaction PredictionPreprint

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DEDTI vs IEDTI: Efficient and Predictive Models of Drug-Target InteractionsPreprint

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Combating COVID-19 by employing machine learning predictions and projections

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Drug-Protein Interaction Prediction via Multi-View Variational Autoencoder and Cascade Deep ForestsPreprint

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A Systematic Review on Drug Interaction Prediction Using Various Methods to Reduce Adverse Effects

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Predicting Drug Target Genes Based on PPI and PDI Networks

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BioNet+: A Comprehensive Interaction Model of Finding Therapeutics for Diseases with Graph Deep Learning

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Additional file 1 of DLDTI: a learning-based framework for drug-target interaction identification using neural networks and network representation

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Additional file 2 of DLDTI: a learning-based framework for drug-target interaction identification using neural networks and network representation

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Drug-Target Interaction Prediction Based on Multi-path Graph Convolution and Graph-Level Attention Mechanism

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GSDPI: An Integrated Feature Extraction Framework for Predicting Novel Drug-Protein Interaction

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Knowledge Graph-Based JingFang Granules Efficacy Analysis for Influenza-Like Illness

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SAGS-DynamicBio: Integrating Semantic-Aware and Graph Structure-Aware Embedding for Dynamic Biological Data with Knowledge Graphs

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Multi-source Data-driven Drug Repositioning based on Deep Self-attention Network

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MBF-DTI: A Fused Multi-dimensional Biochemical Feature-Based Drug Target Prediction Method Based on Heterogeneous Graph Attention Networks

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Metapath-based Feature Aggregated Heterogeneous Graph Neural Network for Adverse Drug Reactions PredictingPreprint

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MGPT: A Multi‐task Graph Prompt Learning Framework for Drug Discovery

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

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Heterogeneous Network With Multiview Path Aggregation: Drug–Target Interaction Prediction Study Design

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ECLIPSE: Exploration of Complex Ligand-Protein Interactions through Learning from Systems-level Heterogeneous Biomedical Knowledge GraphsPreprint

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A Heterogeneous Graph Framework for Inference of Metabolite–Protein-Drug Interaction NetworksPreprint

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DRPMKB1.0: A Comprehensive Knowledge Base for an AI-Oriented Drug Repositioning Prediction Model

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Knowledge Graph

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Survey on Deep Learning Methods in Drug Repurposing

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Low-Rank Approximation Based Multimodal DTI Prediction Model with Hypercomplex Representations

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HyperDTI-Lite: Hyperbolic Geometry for Enhanced Drug-Target Interaction Prediction via Heterogeneous Feature Fusion

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LinkDTI: Drug-Target Interactions prediction through a Link Prediction framework on Biomedical Knowledge GraphPreprint

Mondal, M., Arunachalam, S., Wu, S., & Datta, A. A. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.21.707210

MSANDTI: Multi-Scale Attention Network for Drug-Target Interaction Prediction with Robust Cold-Start Generalization

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CADG-DTA: a deep learning model for drug-target binding affinity prediction, using graph neural networks and cross-attention fusion

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A Confidence‐Aware Ensemble Drug‐Target Interactions Prediction Model With Efficient Adapters

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KAMDA: A multi-view Kolmogorov-Arnold Network integrating pre-trained BERT embeddings and similarity-based imputation for microbe-drug association prediction

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KansFormer network based on a multimodal cross-attention mechanism for drug-target interaction prediction

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BG-δ-K-WLNM: Drug-Target Interaction Prediction Framework Using a Bipartite Graph Model and Local-K-dimensional Weisfeiler Lehman Neural Machine

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Exploring CRISPR/Cas9 Technology for The Modernization of Traditional Chinese Medicine

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CAHNetF-DTP: A Community-Aware Heterogeneous Network-Based Embedding Framework for Drug-Target Interaction Prediction

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KGsteeredDTI: Drug-Target Interaction Prediction via Knowledge Graphs-Steering

Li, X., Zhang, Y., Liu, Y., & Ma, P. (2026) · Lecture notes in computer science · doi:10.1007/978-981-95-7141-3_33

Drug-target interaction prediction via hierarchical gated attention and information bottleneck

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Literature Review: Graph Neural Network–Based Methods for Drug–Protein Interaction Prediction

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Knowledge-graph attention network ChemFlow identifies modulators of EGFR

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STAGE: Semantic-to-Task Graph Enhancement for Heterogeneous Graph Contrastive Learning

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SGH-DTI: Drug-Target Interaction Prediction Based on Sequence Feature Enhancement and Multi-hop Heterogeneous Graph Attention

Liu, C., Li, J., Jiao, C., & Zhu, M. (2026) · Lecture notes in computer science · doi:10.1007/978-981-92-3498-1_18

CSML-DTA: Drug Target Affinity Prediction Based on Cross-Scale and Multi-Level Feature Fusion

Yan, H., Zhao, H., Bai, Y., & Qin, X. (2026) · Lecture notes in computer science · doi:10.1007/978-981-92-3485-1_2

SENT-DTI: Semantic-enhanced drug-target interaction prediction with negative training strategy

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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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AI-driven Approaches for Target Discovery in Drug Design

Iwata, H. (2026) · Royal Society of Chemistry eBooks · doi:10.1039/9781837070206-00039

Path-Induced Regularized Graph Contrastive Learning for Drug-Target Interaction Prediction

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A linear interpretable model for drug target prediction

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Machine Learning‐Aided Small‐Molecule Virtual Screening: Recent Advances and Future Perspectives

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MLI-DTA: An interpretable multimodal framework with multi-level interactions for drug-target affinity prediction

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Regime-aware cross-paradigm distillation for drug-target interaction prediction

Shi, B., Zhang, S., Wu, J., Fang, J., Chen, J., & Yang, J. (2026) · Expert Systems with Applications · doi:10.1016/j.eswa.2026.134888

HGDTI: predicting drug–target interaction by using information aggregation based on heterogeneous graph neural network

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Hnet-DTI: Incorporating heterogeneous information network for drug-target interaction prediction

Özsarı, G., Rifaioğlu, A. S., Doğan, T., & Atalay, V. (2022) · OpenMETU (Middle East Technical University)

Predicting Drug-Target Interactions Over Heterogeneous Information Network

Su, X., Hu, P., Yi, H.-C., You, Z., & Hu, L. (2022) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2022.3219213 · Cited by 66

NGCN : Drug‐target interaction prediction by integrating information and feature learning from heterogeneous network

Cao, J., Chen, Q., Qiu, J., Wang, Y., Lan, W., Du, X., & Tan, K. (2024) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.18224 · Cited by 9

Integrated multi-similarity fusion and heterogeneous graph inference for drug-target interaction prediction

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