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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:

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

Showing 12 citing articles:

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
Recent Studies of Artificial Intelligence on In Silico Drug Distribution Prediction
Thi Tuyet Van Tran, Hilal Tayara, Kil To Chong
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 3, pp. 1815-1815
Open Access | Times Cited: 21
Experimental and Computational Methods to Assess Central Nervous System Penetration of Small Molecules
Mayuri Gupta, Jun Feng, Govinda Bhisetti
Molecules (2024) Vol. 29, Iss. 6, pp. 1264-1264
Open Access | Times Cited: 4
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
An efficient curriculum learning-based strategy for molecular graph learning
Yaowen Gu, Si Zheng, Zidu Xu, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 3
Closed Access | Times Cited: 12
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
On modeling and utilizing chemical compound information with deep learning technologies: A task-oriented approach
Sangsoo Lim, Sangseon Lee, Yinhua Piao, et al.
Computational and Structural Biotechnology Journal (2022) Vol. 20, pp. 4288-4304
Open Access | Times Cited: 9
Predicting Binding Energies and Electronic Properties of Boron Nitride Fullerenes Using a Graph Convolutional Network
Linwei Sai, Fu Li, Jijun Zhao
Journal of Chemical Information and Modeling (2023) Vol. 64, Iss. 7, pp. 2645-2653
Closed Access | Times Cited: 2
DeBERTaSSL: Enhancing Molecular Property Prediction with Self-Supervised Learning
K Ghaayathri Devi, Ravi Shankar Bedadhala, S. Sachin Kumar, et al.
(2024), pp. 1-7
Closed Access
Exploring the potential of artificial intelligence in drug delivery to brain
Shefali Mehla, Girish Chandra Arya, Vimal Arora
Elsevier eBooks (2024), pp. 411-428
Closed Access
Methodology for Hyperparameter Tuning of Deep Neural Networks for Efficient and Accurate Molecular Property Prediction
X. Nguyen, Y.A. Liu
Computers & Chemical Engineering (2024) Vol. 193, pp. 108928-108928
Closed Access
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: 1
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