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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Deep Learning in Drug Target Interaction Prediction: Current and Future Perspectives
Karim Abbasi, Parvin Razzaghi, Antti Poso, et al.
Current Medicinal Chemistry (2020) Vol. 28, Iss. 11, pp. 2100-2113
Closed Access | Times Cited: 71

Showing 1-25 of 71 citing articles:

Machine-learning methods for ligand–protein molecular docking
Kévin Crampon, Alexis Giorkallos, Myrtille Deldossi, et al.
Drug Discovery Today (2021) Vol. 27, Iss. 1, pp. 151-164
Open Access | Times Cited: 215
Artificial intelligence in the prediction of protein–ligand interactions: recent advances and future directions
Ashwin Dhakal, Cole McKay, John J. Tanner, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Open Access | Times Cited: 154
Interpretable bilinear attention network with domain adaptation improves drug–target prediction
Peizhen Bai, Filip Miljković, Bino John, et al.
Nature Machine Intelligence (2023) Vol. 5, Iss. 2, pp. 126-136
Closed Access | Times Cited: 125
DeepTraSynergy: drug combinations using multimodal deep learning with transformers
Fatemeh Rafiei, Hojjat Zeraati, Karim Abbasi, et al.
Bioinformatics (2023) Vol. 39, Iss. 8
Open Access | Times Cited: 40
CFSSynergy: Combining Feature-Based and Similarity-Based Methods for Drug Synergy Prediction
Fatemeh Rafiei, Hojjat Zeraati, Karim Abbasi, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 7, pp. 2577-2585
Closed Access | Times Cited: 26
Artificial intelligence streamlines scientific discovery of drug–target interactions
Yuxin Yang, Feixiong Cheng
British Journal of Pharmacology (2025)
Open Access | Times Cited: 2
An effective self-supervised framework for learning expressive molecular global representations to drug discovery
Pengyong Li, Jun Wang, Yixuan Qiao, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Closed Access | Times Cited: 101
Comprehensive Survey of Recent Drug Discovery Using Deep Learning
Jintae Kim, Sera Park, Dongbo Min, et al.
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 18, pp. 9983-9983
Open Access | Times Cited: 99
How can natural language processing help model informed drug development?: a review
Roopal Bhatnagar, Sakshi Sardar, Maedeh Beheshti, et al.
JAMIA Open (2022) Vol. 5, Iss. 2
Open Access | Times Cited: 43
Pharmacophoric-constrained heterogeneous graph transformer model for molecular property prediction
Yinghui Jiang, Shuting Jin, Xurui Jin, et al.
Communications Chemistry (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 34
Open-Source Machine Learning in Computational Chemistry
Alexander Hagg, Karl N. Kirschner
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 15, pp. 4505-4532
Open Access | Times Cited: 28
A review of deep learning methods for ligand based drug virtual screening
Hongjie Wu, Junkai Liu, Runhua Zhang, et al.
Fundamental Research (2024) Vol. 4, Iss. 4, pp. 715-737
Open Access | Times Cited: 13
G-K BertDTA: A graph representation learning and semantic embedding-based framework for drug-target affinity prediction
Xihe Qiu, Haoyu Wang, Xiaoyu Tan, et al.
Computers in Biology and Medicine (2024) Vol. 173, pp. 108376-108376
Closed Access | Times Cited: 11
Large language models in bioinformatics: applications and perspectives
Jiajia Liu, Mengyuan Yang, Yankai Yu, et al.
arXiv (Cornell University) (2024)
Open Access | Times Cited: 8
GraphsformerCPI: Graph Transformer for Compound–Protein Interaction Prediction
Jun Ma, Zhili Zhao, Tongfeng Li, et al.
Interdisciplinary Sciences Computational Life Sciences (2024) Vol. 16, Iss. 2, pp. 361-377
Closed Access | Times Cited: 8
SAG-DTA: Prediction of Drug–Target Affinity Using Self-Attention Graph Network
Shugang Zhang, Mingjian Jiang, Shuang Wang, et al.
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 16, pp. 8993-8993
Open Access | Times Cited: 41
A Systematic Review of Deep Learning Methodologies Used in the Drug Discovery Process with Emphasis on In Vivo Validation
Nikoletta-Maria Koutroumpa, Konstantinos D. Papavasileiou, Anastasios G. Papadiamantis, et al.
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 7, pp. 6573-6573
Open Access | Times Cited: 19
ZeroBind: a protein-specific zero-shot predictor with subgraph matching for drug-target interactions
Yuxuan Wang, Ying Xia, Junchi Yan, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 19
Deciphering the Molecular Mechanism of Bu Yang Huan Wu Decoction in Interference with Diabetic Pulmonary Fibrosis via Regulating Oxidative Stress and Lipid Metabolism Disorder
Junfeng Guo, Yuwei Zhang, Rui Zhou, et al.
Journal of Pharmaceutical and Biomedical Analysis (2024) Vol. 243, pp. 116061-116061
Closed Access | Times Cited: 5
A comprehensive review of the recent advances on predicting drug-target affinity based on deep learning
Xin Zeng, Shujuan Li, Shuang‐Qing Lv, et al.
Frontiers in Pharmacology (2024) Vol. 15
Open Access | Times Cited: 5
Design of a Scoring System for National Fitness Volunteer Services Under Deep Learning
A. K. Singh, Raghav Singla, Pulkit Sodhi, et al.
Procedia Computer Science (2025) Vol. 252, pp. 653-664
Open Access
Omics Approaches to Drug and Drug-Non-Drug Interactions
Angela Adamski da Silva Reis, Rodrigo da Silva Santos
(2025), pp. 261-290
Closed Access
Recent advances in target identification technology of natural products
Tingting Liu, Ke‐Wu Zeng
Pharmacology & Therapeutics (2025), pp. 108833-108833
Closed Access
AutoDTI++: deep unsupervised learning for DTI prediction by autoencoders
Seyedeh Zahra Sajadi, Mohammad Ali Zare Chahooki, Sajjad Gharaghani, et al.
BMC Bioinformatics (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 32
Comparative Studies on Resampling Techniques in Machine Learning and Deep Learning Models for Drug-Target Interaction Prediction
Azwaar Khan Azlim Khan, Nurul Hashimah Ahamed Hassain Malim
Molecules (2023) Vol. 28, Iss. 4, pp. 1663-1663
Open Access | Times Cited: 12
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