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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:

MG-BERT: leveraging unsupervised atomic representation learning for molecular property prediction
Xiaochen Zhang, Chengkun Wu, Zhijiang Yang, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Closed Access | Times Cited: 111

Showing 1-25 of 111 citing articles:

Chemformer: a pre-trained transformer for computational chemistry
Ross Irwin, Spyridon Dimitriadis, Jiazhen He, et al.
Machine Learning Science and Technology (2021) Vol. 3, Iss. 1, pp. 015022-015022
Open Access | Times Cited: 132
Accurate prediction of molecular properties and drug targets using a self-supervised image representation learning framework
Xiangxiang Zeng, Hongxin Xiang, Linhui Yu, et al.
Nature Machine Intelligence (2022) Vol. 4, Iss. 11, pp. 1004-1016
Open Access | Times Cited: 126
Deep learning methods for molecular representation and property prediction
Zhen Li, Mingjian Jiang, Shuang Wang, et al.
Drug Discovery Today (2022) Vol. 27, Iss. 12, pp. 103373-103373
Closed Access | Times Cited: 120
Attention is all you need: utilizing attention in AI-enabled drug discovery
Yang Zhang, Caiqi Liu, Mujiexin Liu, et al.
Briefings in Bioinformatics (2023) Vol. 25, Iss. 1
Open Access | Times Cited: 109
Organic Compound Synthetic Accessibility Prediction Based on the Graph Attention Mechanism
Jiahui Yu, Jike Wang, Hong Zhao, et al.
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 12, pp. 2973-2986
Closed Access | Times Cited: 40
The prediction of molecular toxicity based on BiGRU and GraphSAGE
Jianping Liu, Xiujuan Lei, Yuchen Zhang, et al.
Computers in Biology and Medicine (2023) Vol. 153, pp. 106524-106524
Closed Access | Times Cited: 24
PharmBERT: a domain-specific BERT model for drug labels
Taha ValizadehAslani, Yiwen Shi, Ping Ren, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 4
Closed Access | Times Cited: 21
Large language models for science and medicine
Amalio Telenti, Michael Auli, Brian Hie, et al.
European Journal of Clinical Investigation (2024) Vol. 54, Iss. 6
Closed Access | Times Cited: 10
Advancing drug discovery with deep attention neural networks
Antonio Lavecchia
Drug Discovery Today (2024) Vol. 29, Iss. 8, pp. 104067-104067
Open Access | Times Cited: 9
A machine learning method to predict rate constants for various reactions in combustion kinetic models
Ning Li, Sanket Girhe, Mingzhi Zhang, et al.
Combustion and Flame (2024) Vol. 263, pp. 113375-113375
Closed Access | Times Cited: 8
Pushing the Boundaries of Molecular Property Prediction for Drug Discovery with Multitask Learning BERT Enhanced by SMILES Enumeration
Xiaochen Zhang, Chengkun Wu, Jiacai Yi, et al.
Research (2022) Vol. 2022
Open Access | Times Cited: 35
TransFoxMol: predicting molecular property with focused attention
Jian Gao, Zheyuan Shen, Yufeng Xie, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 5
Closed Access | Times Cited: 20
SolvBERT for solvation free energy and solubility prediction: a demonstration of an NLP model for predicting the properties of molecular complexes
Jiahui Yu, Chengwei Zhang, Yingying Cheng, et al.
Digital Discovery (2023) Vol. 2, Iss. 2, pp. 409-421
Open Access | Times Cited: 18
Recent Applications of Machine Learning in Molecular Property and Chemical Reaction Outcome Predictions
Shilpa Shilpa, Gargee Kashyap, Raghavan B. Sunoj
The Journal of Physical Chemistry A (2023) Vol. 127, Iss. 40, pp. 8253-8271
Closed Access | Times Cited: 15
FG-BERT: a generalized and self-supervised functional group-based molecular representation learning framework for properties prediction
Biaoshun Li, Mujie Lin, Tiegen Chen, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 6
Closed Access | Times Cited: 15
Crystal Composition Transformer: Self‐Learning Neural Language Model for Generative and Tinkering Design of Materials
Lai Wei, Qinyang Li, Yuqi Song, et al.
Advanced Science (2024)
Open Access | Times Cited: 6
Can large language models understand molecules?
Shaghayegh Sadeghi, Alan Bui, Ali Forooghi, et al.
BMC Bioinformatics (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 5
CLSSATP: Contrastive learning and self-supervised learning model for aquatic toxicity prediction
Lin Ye, Xin Yang, Mingxuan Zhang, et al.
Aquatic Toxicology (2025) Vol. 279, pp. 107244-107244
Closed Access
A Dual-View Deep Learning-Driven Discovery of Cinnamoyl Anthranilic Acid Derivatives Against Orthopoxvirus Through Targeting Host Itgb3
Yanxiang Wang, Mengyi Xu, Fan Liu, et al.
(2025)
Closed Access
Positional embeddings and zero-shot learning using BERT for molecular-property prediction
Medard Edmund Mswahili, JunHa Hwang, Jagath C. Rajapakse, et al.
Journal of Cheminformatics (2025) Vol. 17, Iss. 1
Open Access
MDFCL: Multimodal data fusion-based graph contrastive learning framework for molecular property prediction
Xu Gong, Maotao Liu, Qun Liu, et al.
Pattern Recognition (2025), pp. 111463-111463
Closed Access
RAG_MCNNIL6: A Retrieval-Augmented Multi-Window Convolutional Network for Accurate Prediction of IL-6 Inducing Epitopes
Cheng-Che Chuang, Yu-Chen Liu, Won-Kyoung Jhang, et al.
Journal of Chemical Information and Modeling (2025)
Open Access
Learning to SMILES: BAN-based strategies to improve latent representation learning from molecules
Chengkun Wu, Xiaochen Zhang, Zhijiang Yang, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Closed Access | Times Cited: 38
Chemformer: A Pre-Trained Transformer for Computational Chemistry
Ross Irwin, Spyridon Dimitriadis, Jiazhen He, et al.
(2021)
Open Access | Times Cited: 37
DeepReac+: deep active learning for quantitative modeling of organic chemical reactions
Yukang Gong, Dongyu Xue, Guohui Chuai, et al.
Chemical Science (2021) Vol. 12, Iss. 43, pp. 14459-14472
Open Access | Times Cited: 36
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