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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:

Quantitative evaluation of explainable graph neural networks for molecular property prediction
Jiahua Rao, Shuangjia Zheng, Yutong Lu, et al.
Patterns (2022) Vol. 3, Iss. 12, pp. 100628-100628
Open Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

Federated learning-based AI approaches in smart healthcare: concepts, taxonomies, challenges and open issues
Anichur Rahman, Md. Sazzad Hossain, Ghulam Muhammad, et al.
Cluster Computing (2022) Vol. 26, Iss. 4, pp. 2271-2311
Open Access | Times Cited: 154
Chemistry-intuitive explanation of graph neural networks for molecular property prediction with substructure masking
Zhenhua Wu, Jike Wang, Hongyan Du, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 64
A Perspective on Explanations of Molecular Prediction Models
Geemi P. Wellawatte, Heta A. Gandhi, Aditi Seshadri, et al.
Journal of Chemical Theory and Computation (2023) Vol. 19, Iss. 8, pp. 2149-2160
Open Access | Times Cited: 46
Explainable Artificial Intelligence for Drug Discovery and Development: A Comprehensive Survey
Roohallah Alizadehsani, Solomon Sunday Oyelere, Sadiq Hussain, et al.
IEEE Access (2024) Vol. 12, pp. 35796-35812
Open Access | Times Cited: 21
Explainable uncertainty quantifications for deep learning-based molecular property prediction
Chu-I Yang, Yi‐Pei Li
Journal of Cheminformatics (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 29
Identifying spatial domain by adapting transcriptomics with histology through contrastive learning
Yuansong Zeng, Rui Yin, Mai Luo, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 2
Open Access | Times Cited: 27
Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence
Miquel Duran‐Frigola, Marko Cigler, Georg E. Winter
Journal of the American Chemical Society (2023) Vol. 145, Iss. 5, pp. 2711-2732
Open Access | Times Cited: 20
Identifying B-cell epitopes using AlphaFold2 predicted structures and pretrained language model
Yuansong Zeng, Zhuoyi Wei, Qianmu Yuan, et al.
Bioinformatics (2023) Vol. 39, Iss. 4
Open Access | Times Cited: 20
From intuition to AI: evolution of small molecule representations in drug discovery
Miles McGibbon, Steven Shave, Jie Dong, et al.
Briefings in Bioinformatics (2023) Vol. 25, Iss. 1
Open Access | Times Cited: 20
Multi-order graph attention network for water solubility prediction and interpretation
Sangho Lee, Hyun‐Woo Park, Chihyeon Choi, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 15
Machine Learning‐Aided Design of Highly Conductive Anion Exchange Membranes for Fuel Cells and Water Electrolyzers
Qiuhuan Zhang, Yongjiang Yuan, Jiale Zhang, et al.
Advanced Materials (2024)
Open Access | Times Cited: 6
Enhancing property and activity prediction and interpretation using multiple molecular graph representations with MMGX
Apakorn Kengkanna, Masahito Ohue
Communications Chemistry (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 5
MMGCF: Generating Counterfactual Explanations for Molecular Property Prediction via Motif Rebuild
Xiuping Zhang, Qun Liu, R. Han
Journal of Computer and Communications (2025) Vol. 13, Iss. 01, pp. 152-168
Open Access
Insights into Quantitative Evaluation Techniques for AI Explainability
Hugo Siqueira Gomes, Jo�ão José Pinto Ferreira, Manuel Rodrigues
Lecture notes in networks and systems (2025), pp. 292-306
Closed Access
A small-scale data driven and graph neural network based toxicity prediction method of compounds
Xin Zhao, Shuyi Zhang, Tao Zhang, et al.
Computational Biology and Chemistry (2025) Vol. 117, pp. 108393-108393
Closed Access
GraphXAI: a survey of graph neural networks (GNNs) for explainable AI (XAI)
Mauparna Nandan, Soma Mitra, Debashis De
Neural Computing and Applications (2025)
Closed Access
Selective functionalization of hindered meta-C–H bond of o-alkylaryl ketones promoted by automation and deep learning
Jia Qiu, Jiancong Xie, Shimin Su, et al.
Chem (2022) Vol. 8, Iss. 12, pp. 3275-3287
Open Access | Times Cited: 23
Explainable artificial intelligence: A taxonomy and guidelines for its application to drug discovery
Ignacio Ponzoni, Juan Antonio Páez Prosper, Nuria E. Campillo
Wiley Interdisciplinary Reviews Computational Molecular Science (2023) Vol. 13, Iss. 6
Closed Access | Times Cited: 14
Application scenario-oriented molecule generation platform developed for drug discovery
Lianjun Zheng, Fangjun Shi, Chunwang Peng, et al.
Methods (2024) Vol. 222, pp. 112-121
Closed Access | Times Cited: 4
Revolutionizing GPCR–ligand predictions: DeepGPCR with experimental validation for high-precision drug discovery
Haiping Zhang, Hongjie Fan, Jixia Wang, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 4
Open Access | Times Cited: 4
AMPred-CNN: Ames mutagenicity prediction model based on convolutional neural networks
Thi Tuyet Van Tran, Hilal Tayara, Kil To Chong
Computers in Biology and Medicine (2024) Vol. 176, pp. 108560-108560
Closed Access | Times Cited: 3
Cross‐Modal Graph Contrastive Learning with Cellular Images
Shuangjia Zheng, Jiahua Rao, Jixian Zhang, et al.
Advanced Science (2024) Vol. 11, Iss. 32
Open Access | Times Cited: 2
Interpretable Attribution Assignment for Octanol–Water Partition Coefficient
Daisuke Yokogawa, Kayo Suda
The Journal of Physical Chemistry B (2023) Vol. 127, Iss. 31, pp. 7004-7010
Closed Access | Times Cited: 7
Explaining compound activity predictions with a substructure-aware loss for graph neural networks
Kenza Amara, Raquel Rodríguez-Pérez, José Jiménez-Luna
Journal of Cheminformatics (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 5
Towards explainable motion prediction using heterogeneous graph representations
Sandra Carrasco Limeros, Sylwia Majchrowska, Joakim Johnander, et al.
Transportation Research Part C Emerging Technologies (2023) Vol. 157, pp. 104405-104405
Open Access | Times Cited: 5
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