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Drug target binding affinity (DTA) is a key criterion for drug screening.
High-throughput screening: new technology for the 21st century
Robert P Hertzberg and Andrew J Pope · 2000
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Simplified molecular input line entry system (smiles) as an alternative for constructing quantitative structure-property relationships (qspr)
Andrey A Toropov et al · 2005
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Greg Landrum · 2006
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A machine learning approach to predicting protein–ligand binding affinity with applications to molecular docking
Pedro J Ballester et al · 2010
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Comprehensive analysis of kinase inhibitor selectivity
Mindy I Davis et al · 2011
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Hhblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
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Making sense of large-scale kinase inhibitor bioactivity data sets: a comparative and integrative analysis
Jing Tang et al · 2014
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Toward more realistic drug–target interaction predictions
Tapio Pahikkala et al · 2015
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Simboost: a read-across approach for predicting drug–target binding affinities using gradient boosting machines
Tong He et al · 2017
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Multi-view learning overview: Recent progress and new challenges
Jing Zhao et al · 2017
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Deepdta: deep drug–target binding affinity prediction
Hakime Öztürk et al · 2018
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Pconsc4: fast, accurate and hassle-free contact predictions
Mirco Michel et al · 2019
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Molecular docking: shifting paradigms in drug discovery
Luca Pinzi and Giulio Rastelli · 2019
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Comparison study of computational prediction tools for drug-target binding affinities
Maha Thafar et al · 2019
Cited alongside, same era.
AttentionDTA: prediction of drug–target binding affinity using attention model
Qichang Zhao et al · 2019
Cited alongside, same era.
Drug–target affinity prediction using graph neural network and contact maps
Mingjian Jiang et al · 2020
Cited alongside, same era.
GansDTA: Predicting drug-target binding affinity using GANs
Lingling Zhao et al · 2020
Cited alongside, same era.
The power of scale for parameter-efficient prompt tuning
Brian Lester et al · 2021
Cited alongside, same era.
GraphDTA: predicting drug–target binding affinity with graph neural networks
MgraphDTA: deep multiscale graph neural network for explainable drug–target binding affinity prediction
Ziduo Yang et al · 2022
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Predicting drug–target binding affinity through molecule representation block based on multi-head attention and skip connection
Li Zhang et al · 2022
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Learning to prompt for vision-language models
Kaiyang Zhou et al · 2022
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FingerDTA: a fingerprint-embedding framework for drug-target binding affinity prediction
Xuekai Zhu et al · 2022
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Ma-gcl: Model augmentation tricks for graph contrastive learning
Xumeng Gong et al · 2023
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Mfr-DTA: a multi-functional and robust model for predicting drug–target binding affinity and region
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Thin Nguyen et al · 2021
Cited alongside, same era.
DeepFusionDTA: drug-target binding affinity prediction with information fusion and hybrid deep-learning ensemble model
Yuqian Pu et al · 2021
Cited alongside, same era.
MultiscaleDTA: A multiscale-based method with a self-attention mechanism for drug-target binding affinity prediction
Haoyang Chen et al · 2022
Cited alongside, same era.
Hierarchical graph representation learning for the prediction of drug-target binding affinity
Zhaoyang Chu et al · 2022
Cited alongside, same era.
Visual prompt tuning
Menglin Jia et al · 2022
Cited alongside, same era.
Denseclip: Language-guided dense prediction with context-aware prompting
Yongming Rao et al · 2022
Cited alongside, same era.
Deep Learning in Drug Design: Protein-Ligand Binding Affinity Prediction
Mohammad A. Rezaei et al · 2022
Cited alongside, same era.
Yang Hua et al · 2023
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BiComp-DTA: Drug-target binding affinity prediction through complementary biological-related and compression-based featurization approach
Mahmood Kalemati et al · 2023
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Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing
Pengfei Liu et al · 2023
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Predicting drug-target affinity by learning protein knowledge from biological networks
Wenjian Ma et al · 2023
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DoubleSG-DTA: Deep Learning for Drug Discovery: Case Study on the Non-Small Cell Lung Cancer with EGFR T 790 M Mutation
Yongtao Qian et al · 2023
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3dprotDTA: a deep learning model for drug-target affinity prediction based on residue-level protein graphs
Taras Voitsitskyi et al · 2023
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Hsgcl-DTA: Hybrid-scale Graph Contrastive Learning based Drug-Target Binding Affinity Prediction
Hongyan Ye et al · 2023
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