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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:

Comparison Study of Computational Prediction Tools for Drug-Target Binding Affinities
Maha A. Thafar, Arwa Bin Raies, Somayah Albaradei, et al.
Frontiers in Chemistry (2019) Vol. 7
Open Access | Times Cited: 124

Showing 1-25 of 124 citing articles:

Artificial intelligence in drug discovery and development
Debleena Paul, Gaurav Sanap, Snehal Shenoy, et al.
Drug Discovery Today (2020) Vol. 26, Iss. 1, pp. 80-93
Open Access | Times Cited: 1023
Deep learning in drug discovery: an integrative review and future challenges
Heba Askr, Enas Elgeldawi, Heba Aboul Ella, et al.
Artificial Intelligence Review (2022) Vol. 56, Iss. 7, pp. 5975-6037
Open Access | Times Cited: 180
PIGNet: a physics-informed deep learning model toward generalized drug–target interaction predictions
Seokhyun Moon, Wonho Zhung, Soojung Yang, et al.
Chemical Science (2022) Vol. 13, Iss. 13, pp. 3661-3673
Open Access | Times Cited: 121
Deep learning tools for advancing drug discovery and development
Sagorika Nag, Anurag T. K. Baidya, Abhimanyu Mandal, et al.
3 Biotech (2022) Vol. 12, Iss. 5
Open Access | Times Cited: 103
Artificial intelligence in cancer diagnosis and therapy: Current status and future perspective
Muhammad Sufyan, Zeeshan Shokat, Usman Ali Ashfaq
Computers in Biology and Medicine (2023) Vol. 165, pp. 107356-107356
Closed Access | Times Cited: 66
Design and Prediction of Aptamers Assisted by In Silico Methods
Su Jin Lee, Junmin Cho, Byung‐Hoon Lee, et al.
Biomedicines (2023) Vol. 11, Iss. 2, pp. 356-356
Open Access | Times Cited: 41
DTiGEMS+: drug–target interaction prediction using graph embedding, graph mining, and similarity-based techniques
Maha A. Thafar, Rawan S. Olayan, Haitham Ashoor, et al.
Journal of Cheminformatics (2020) Vol. 12, Iss. 1
Open Access | Times Cited: 118
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: 100
MDeePred: novel multi-channel protein featurization for deep learning-based binding affinity prediction in drug discovery
Ahmet Süreyya Rifaioğlu, Rengül Çetin-Atalay, Deniz Kahraman, et al.
Bioinformatics (2020) Vol. 37, Iss. 5, pp. 693-704
Closed Access | Times Cited: 85
Deep learning allows genome-scale prediction of Michaelis constants from structural features
Alexander Kroll, Martin K. M. Engqvist, David Heckmann, et al.
PLoS Biology (2021) Vol. 19, Iss. 10, pp. e3001402-e3001402
Open Access | Times Cited: 82
Artificial Intelligence in Aptamer–Target Binding Prediction
Zihao Chen, Long Hu, Bao‐Ting Zhang, et al.
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 7, pp. 3605-3605
Open Access | Times Cited: 72
AttentionSiteDTI: an interpretable graph-based model for drug-target interaction prediction using NLP sentence-level relation classification
Mehdi Yazdani-Jahromi, Niloofar Yousefi, Aida Tayebi, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 4
Open Access | Times Cited: 67
GEFA: Early Fusion Approach in Drug-Target Affinity Prediction
Tri Minh Nguyen, Thin Nguyen, Thao Minh Le, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2021) Vol. 19, Iss. 2, pp. 718-728
Open Access | Times Cited: 66
Affinity2Vec: drug-target binding affinity prediction through representation learning, graph mining, and machine learning
Maha A. Thafar, Mona Alshahrani, Somayah Albaradei, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 53
Hierarchical graph representation learning for the prediction of drug-target binding affinity
Zhaoyang Chu, Feng Huang, Haitao Fu, et al.
Information Sciences (2022) Vol. 613, pp. 507-523
Open Access | Times Cited: 45
Modality-DTA: Multimodality Fusion Strategy for Drug–Target Affinity Prediction
Xixi Yang, Zhangming Niu, Yuansheng Liu, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2022) Vol. 20, Iss. 2, pp. 1200-1210
Closed Access | Times Cited: 42
Advances in Artificial Intelligence (AI)-assisted approaches in drug screening
Samvedna Singh, Himanshi Gupta, Priyanshu Sharma, et al.
Artificial Intelligence Chemistry (2023) Vol. 2, Iss. 1, pp. 100039-100039
Open Access | Times Cited: 37
Advancing Drug Safety in Drug Development: Bridging Computational Predictions for Enhanced Toxicity Prediction
Ana M. B. Amorim, Luiz F. Piochi, Ana Teresa Gaspar, et al.
Chemical Research in Toxicology (2024) Vol. 37, Iss. 6, pp. 827-849
Open Access | Times Cited: 14
GraphCL-DTA: A Graph Contrastive Learning With Molecular Semantics for Drug-Target Binding Affinity Prediction
Xinxing Yang, Genke Yang, Jian Chu
IEEE Journal of Biomedical and Health Informatics (2024) Vol. 28, Iss. 8, pp. 4544-4552
Open Access | Times Cited: 10
Progress of machine learning in the application of small molecule druggability prediction
Junyao Li, Jianmei Zhang, Rui Guo, et al.
European Journal of Medicinal Chemistry (2025) Vol. 285, pp. 117269-117269
Closed Access | Times Cited: 1
DTi2Vec: Drug–target interaction prediction using network embedding and ensemble learning
Maha A. Thafar, Rawan S. Olayan, Somayah Albaradei, et al.
Journal of Cheminformatics (2021) Vol. 13, Iss. 1
Open Access | Times Cited: 55
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
SS-GNN: A Simple-Structured Graph Neural Network for Affinity Prediction
Shuke Zhang, Yanzhao Jin, Tianmeng Liu, et al.
ACS Omega (2023) Vol. 8, Iss. 25, pp. 22496-22507
Open Access | Times Cited: 17
3DProtDTA: a deep learning model for drug-target affinity prediction based on residue-level protein graphs
Taras Voitsitskyi, Roman Stratiichuk, Ihor Koleiev, et al.
RSC Advances (2023) Vol. 13, Iss. 15, pp. 10261-10272
Open Access | Times Cited: 16
BindingSite-AugmentedDTA: enabling a next-generation pipeline for interpretable prediction models in drug repurposing
Niloofar Yousefi, Mehdi Yazdani-Jahromi, Aida Tayebi, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 3
Open Access | Times Cited: 16
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