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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:

Different molecular enumeration influences in deep learning: an example using aqueous solubility
Jen‐Hao Chen, Yufeng Jane Tseng
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Closed Access | Times Cited: 25

Showing 25 citing articles:

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
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
Recent Advances in Quantum Computing for Drug Discovery and Development
Peihua Wang, Jen‐Hao Chen, Yu-Yuan Yang, et al.
IEEE Nanotechnology Magazine (2023) Vol. 17, Iss. 2, pp. 26-30
Closed Access | Times Cited: 27
Intelligent De Novo Design of Novel Antimicrobial Peptides against Antibiotic-Resistant Bacteria Strains
Tzu-Tang Lin, Li-Yen Yang, Chung‐Yen Lin, et al.
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 7, pp. 6788-6788
Open Access | Times Cited: 21
Improvement of Prediction Performance With Conjoint Molecular Fingerprint in Deep Learning
Liangxu Xie, Lei Xu, Ren Kong, et al.
Frontiers in Pharmacology (2020) Vol. 11
Open Access | Times Cited: 49
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: 40
When Machine Learning and Deep Learning Come to the Big Data in Food Chemistry
Yufeng Jane Tseng, Pei-Jiun Chuang, Michael Appell
ACS Omega (2023) Vol. 8, Iss. 18, pp. 15854-15864
Open Access | Times Cited: 19
Will we ever be able to accurately predict solubility?
Pierre Llompart, Claire Minoletti, Shamkhal Baybekov, et al.
Scientific Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 6
MRFF-YOLO: A Multi-Receptive Fields Fusion Network for Remote Sensing Target Detection
Danqing Xu, Yiquan Wu
Remote Sensing (2020) Vol. 12, Iss. 19, pp. 3118-3118
Open Access | Times Cited: 30
Recent Advances in Toxicity Prediction: Applications of Deep Graph Learning
Yuwei Miao, Hehuan Ma, Junzhou Huang
Chemical Research in Toxicology (2023) Vol. 36, Iss. 8, pp. 1206-1226
Closed Access | Times Cited: 8
INTransformer: Data augmentation-based contrastive learning by injecting noise into transformer for molecular property prediction
Jing Jiang, Yachao Li, Ruisheng Zhang, et al.
Journal of Molecular Graphics and Modelling (2024) Vol. 128, pp. 108703-108703
Closed Access | Times Cited: 2
Detection of microalgae objects based on the Improved YOLOv3 model
Mengying Cao, Junsheng Wang, Yantong Chen, et al.
Environmental Science Processes & Impacts (2021) Vol. 23, Iss. 10, pp. 1516-1530
Closed Access | Times Cited: 17
On Approximating the pIC50 Value of COVID-19 Medicines In Silico with Artificial Neural Networks
Sandi Baressi Šegota, Ivan Lorencin, Zoran Kovač, et al.
Biomedicines (2023) Vol. 11, Iss. 2, pp. 284-284
Open Access | Times Cited: 6
Analysis of Training and Seed Bias in Small Molecules Generated with a Conditional Graph-Based Variational Autoencoder─Insights for Practical AI-Driven Molecule Generation
Seung-Gu Kang, Joseph A. Morrone, Jeffrey K. Weber, et al.
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 4, pp. 801-816
Open Access | Times Cited: 10
NoiseMol: A noise-robusted data augmentation via perturbing noise for molecular property prediction
Jing Jiang, Ruisheng Zhang, Yongna Yuan, et al.
Journal of Molecular Graphics and Modelling (2023) Vol. 121, pp. 108454-108454
Closed Access | Times Cited: 5
Applications of artificial intelligence to lipid nanoparticle delivery
Ye Yuan, Yuqi Wu, Jiabei Cheng, et al.
Particuology (2023) Vol. 90, pp. 88-97
Open Access | Times Cited: 5
Discovering Novel Antimicrobial Peptides in Generative Adversarial Network
Tzu-Tang Lin, Li-Yen Yang, Ching-Tien Wang, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 13
A general optimization protocol for molecular property prediction using a deep learning network
Jen‐Hao Chen, Yufeng Jane Tseng
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Open Access | Times Cited: 12
Machine learning and deep learning enabled fuel sooting tendency prediction from molecular structure
Runzhao Li, J.M. Herreros, A. Tsolakis, et al.
Journal of Molecular Graphics and Modelling (2021) Vol. 111, pp. 108083-108083
Open Access | Times Cited: 9
Recent Studies of Artificial Intelligence on In Silico Drug Absorption
Thi Tuyet Van Tran, Hilal Tayara, Kil To Chong
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 20, pp. 6198-6211
Closed Access | Times Cited: 2
De Novo Drug Property Prediction using Graph Convolutional Neural Networks
Fairuz Shadmani Shishir, Khan Md. Hasib, Shadman Sakib, et al.
(2021), pp. 01-06
Closed Access | Times Cited: 6
Impact of Domain Knowledge and Multi-Modality on Intelligent Molecular Property Prediction: A Systematic Survey
Taojie Kuang, Pengfei Liu, Zhixiang Ren
Big Data Mining and Analytics (2024) Vol. 7, Iss. 3, pp. 858-888
Open Access
The Application of Machine Learning in Predicting the Permeability of Drugs Across the Blood Brain Barrier
Sogand Jafarpour, Maryam Asefzadeh, Ehsan Aboutaleb
Deleted Journal (2024) Vol. 23, Iss. 1
Open Access
On Complementary Approaches of Assessing the Predictive Potential of QSPR/QSAR Models
Andrey A. Toropov, Alla P. Toropova, Danuta Leszczyńska, et al.
Challenges and advances in computational chemistry and physics (2023), pp. 397-420
Closed Access
Analysis of training and seed bias in small molecules generated with a conditional graph-based variational autoencoder -- Insights for practical AI-driven molecule generation
Seung-Gu Kang, Joseph A. Morrone, Jeffrey K. Weber, et al.
arXiv (Cornell University) (2021)
Open Access
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