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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:

DeepACTION: A deep learning-based method for predicting novel drug-target interactions
Saifuddin Mahmud, Wenyu Chen, Hosney Jahan, et al.
Analytical Biochemistry (2020) Vol. 610, pp. 113978-113978
Closed Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

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
Convolutional neural networks (CNNs): concepts and applications in pharmacogenomics
Joel Markus Vaz, S. Balaji
Molecular Diversity (2021) Vol. 25, Iss. 3, pp. 1569-1584
Open Access | Times Cited: 43
A comprehensive review on recent approaches for cancer drug discovery associated with artificial intelligence
Sanjeevi Pandiyan, Li Wang
Computers in Biology and Medicine (2022) Vol. 150, pp. 106140-106140
Closed Access | Times Cited: 25
Deep learning-based discovery of compounds for blood pressure lowering effects
Rongzhen Li, Teh-Lu Wu, Xiaotian Xu, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Machine Learning Approaches in Metabolic Pathway Predictions and Drug-Target Interactions: Advancing Drug Discovery
Mohamed E. Hasan, Ramanjaneyulu Allam, Alaa A. Hemeida, et al.
(2025), pp. 471-496
Closed Access
SynthMol: A Drug Safety Prediction Framework Integrating Graph Attention and Molecular Descriptors into Pre-Trained Geometric Models
Zidong Su, Rong Zhang, Xiaoyu Fan, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access
Multi-TransDTI: Transformer for Drug–Target Interaction Prediction Based on Simple Universal Dictionaries with Multi-View Strategy
Gan Wang, Xudong Zhang, Pan Zheng, et al.
Biomolecules (2022) Vol. 12, Iss. 5, pp. 644-644
Open Access | Times Cited: 19
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
A compact review of progress and prospects of deep learning in drug discovery
Huijun Li, Lin Zou, Jamal A.H. Kowah, et al.
Journal of Molecular Modeling (2023) Vol. 29, Iss. 4
Closed Access | Times Cited: 11
PointGAT: A Quantum Chemical Property Prediction Model Integrating Graph Attention and 3D Geometry
Rong Zhang, Rongqing Yuan, Boxue Tian
Journal of Chemical Theory and Computation (2024) Vol. 20, Iss. 10, pp. 4115-4128
Open Access | Times Cited: 4
DeepBindBC: A practical deep learning method for identifying native-like protein-ligand complexes in virtual screening
Haiping Zhang, Tingting Zhang, Konda Mani Saravanan, et al.
Methods (2022) Vol. 205, pp. 247-262
Closed Access | Times Cited: 18
LGBMDF: A cascade forest framework with LightGBM for predicting drug-target interactions
Yu Peng, Shouwei Zhao, Zhiliang Zeng, et al.
Frontiers in Microbiology (2023) Vol. 13
Open Access | Times Cited: 9
Deep Learning Based Methods for Molecular Similarity Searching: A Systematic Review
Maged Nasser, Umi Kalsom Yusof, Naomie Salim
Processes (2023) Vol. 11, Iss. 5, pp. 1340-1340
Open Access | Times Cited: 8
Small molecule-mediated targeting of microRNAs for drug discovery: Experiments, computational techniques, and disease implications
Jianfeng Sun, Miaoer Xu, Jinlong Ru, et al.
European Journal of Medicinal Chemistry (2023) Vol. 257, pp. 115500-115500
Open Access | Times Cited: 8
Drug-Target Interaction Prediction via Graph Auto-Encoder and Multi-Subspace Deep Neural Networks
Qing Ye, Xiaolong Zhang, Xiaoli Lin
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2022) Vol. 20, Iss. 5, pp. 2647-2658
Closed Access | Times Cited: 13
Machine learning in computational modelling of membrane protein sequences and structures: From methodologies to applications
Jianfeng Sun, A. Kulandaisamy, Jacklyn Liu, et al.
Computational and Structural Biotechnology Journal (2023) Vol. 21, pp. 1205-1226
Open Access | Times Cited: 7
A Novel Autoencoder-Based Feature Selection Method for Drug-Target Interaction Prediction with Human-Interpretable Feature Weights
Gözde Özsert Yiğit, Cesur Baransel
Symmetry (2023) Vol. 15, Iss. 1, pp. 192-192
Open Access | Times Cited: 6
DeepDNAbP: A deep learning-based hybrid approach to improve the identification of deoxyribonucleic acid-binding proteins
Md. Faruk Hosen, Saifuddin Mahmud, Kawsar Ahmed, et al.
Computers in Biology and Medicine (2022) Vol. 145, pp. 105433-105433
Closed Access | Times Cited: 9
Network‐Based Approaches for Drug Repositioning
Tao Song, Gan Wang, Mao Ding, et al.
Molecular Informatics (2021) Vol. 41, Iss. 5
Closed Access | Times Cited: 12
Generating and screeningde novocompounds against given targets using ultrafast deep learning models as core components
Haiping Zhang, Konda Mani Saravanan, Yang Yang, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 4
Closed Access | Times Cited: 8
State-of-the-art Application of Artificial Intelligence to Transporter-centered Functional and Pharmaceutical Research
Jiayi Yin, Nanxin You, Fengcheng Li, et al.
Current Drug Metabolism (2023) Vol. 24, Iss. 3, pp. 162-174
Closed Access | Times Cited: 4
TeM-DTBA: time-efficient drug target binding affinity prediction using multiple modalities with Lasso feature selection
Tanya Liyaqat, Tanvir Ahmad, Chandni Saxena
Journal of Computer-Aided Molecular Design (2023) Vol. 37, Iss. 12, pp. 573-584
Closed Access | Times Cited: 3
Identifying Drug–Target Interactions Through a Combined Graph Attention Mechanism and Self-attention Sequence Embedding Model
Kang Wang, Jing Hu, Xiaolong Zhang
Lecture notes in computer science (2023), pp. 246-257
Closed Access | Times Cited: 2
AI's role in pharmaceuticals: Assisting drug design from protein interactions to drug development
Solene Bechelli, Jérôme Delhommelle
Artificial Intelligence Chemistry (2023) Vol. 2, Iss. 1, pp. 100038-100038
Open Access | Times Cited: 2
Multi source deep learning method for drug-protein interaction prediction using k-mers and chaos game representation
Hengame Abbasi Mesrabadi, Karim Faez, Jamshid Pirgazi
Chemometrics and Intelligent Laboratory Systems (2024) Vol. 246, pp. 105065-105065
Closed Access
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