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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:

The impact of compound library size on the performance of scoring functions for structure-based virtual screening
Louison Fresnais, Pedro J. Ballester
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Open Access | Times Cited: 41

Showing 1-25 of 41 citing articles:

New machine learning and physics-based scoring functions for drug discovery
Isabella Alvim Guedes, André M. S. Barreto, Diogo Marinho, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 156
Machine‐learning scoring functions for structure‐based virtual screening
Hongjian Li, Kam‐Heung Sze, Gang Lü, et al.
Wiley Interdisciplinary Reviews Computational Molecular Science (2020) Vol. 11, Iss. 1
Closed Access | Times Cited: 141
A practical guide to machine-learning scoring for structure-based virtual screening
Viet‐Khoa Tran‐Nguyen, Muhammad Junaid, Saw Simeon, et al.
Nature Protocols (2023) Vol. 18, Iss. 11, pp. 3460-3511
Closed Access | Times Cited: 37
Delta Machine Learning to Improve Scoring-Ranking-Screening Performances of Protein–Ligand Scoring Functions
Chao Yang, Yingkai Zhang
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 11, pp. 2696-2712
Open Access | Times Cited: 43
Recent progress on the prospective application of machine learning to structure-based virtual screening
Ghita Ghislat, Taufiq Rahman, Pedro J. Ballester
Current Opinion in Chemical Biology (2021) Vol. 65, pp. 28-34
Open Access | Times Cited: 47
Machine Learning and Artificial Intelligence: A Paradigm Shift in Big Data-Driven Drug Design and Discovery
Purvashi Pasrija, Prakash Jha, Pruthvi Upadhyaya, et al.
Current Topics in Medicinal Chemistry (2022) Vol. 22, Iss. 20, pp. 1692-1727
Closed Access | Times Cited: 28
Beware of Simple Methods for Structure-Based Virtual Screening: The Critical Importance of Broader Comparisons
Viet‐Khoa Tran‐Nguyen, Pedro J. Ballester
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 5, pp. 1401-1405
Open Access | Times Cited: 15
Comprehensive machine learning boosts structure-based virtual screening for PARP1 inhibitors
Klaudia Caba, Viet‐Khoa Tran‐Nguyen, Taufiq Rahman, et al.
Journal of Cheminformatics (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 4
Selecting machine-learning scoring functions for structure-based virtual screening
Pedro J. Ballester
Drug Discovery Today Technologies (2019) Vol. 32-33, pp. 81-87
Open Access | Times Cited: 48
Featurization strategies for protein–ligand interactions and their applications in scoring function development
Guo‐Li Xiong, Chao Shen, Ziyi Yang, et al.
Wiley Interdisciplinary Reviews Computational Molecular Science (2021) Vol. 12, Iss. 2
Closed Access | Times Cited: 37
The impact of cross-docked poses on performance of machine learning classifier for protein–ligand binding pose prediction
Chao Shen, Xueping Hu, Junbo Gao, et al.
Journal of Cheminformatics (2021) Vol. 13, Iss. 1
Open Access | Times Cited: 35
SCORCH: Improving structure-based virtual screening with machine learning classifiers, data augmentation, and uncertainty estimation
Miles McGibbon, Sam Money-Kyrle, Vincent Blay, et al.
Journal of Advanced Research (2022) Vol. 46, pp. 135-147
Open Access | Times Cited: 24
Large-Scale Docking in the Cloud
Benjamin I. Tingle, John J. Irwin
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 9, pp. 2735-2741
Open Access | Times Cited: 13
Scaffold Splits Overestimate Virtual Screening Performance
Qianrong Guo, Saiveth Hernández-Hernández, Pedro J. Ballester
Lecture notes in computer science (2024), pp. 58-72
Closed Access | Times Cited: 3
Target-Specific Machine Learning Scoring Function Improved Structure-Based Virtual Screening Performance for SARS-CoV-2 Drugs Development
Muhammad Tahir ul Qamar, Xi-Tong Zhu, Ling‐Ling Chen, et al.
International Journal of Molecular Sciences (2022) Vol. 23, Iss. 19, pp. 11003-11003
Open Access | Times Cited: 18
Conformal prediction of molecule-induced cancer cell growth inhibition challenged by strong distribution shifts
Saiveth Hernández-Hernández, Qianrong Guo, Pedro J. Ballester
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 3
Evolution of Artificial Intelligence-Powered Technologies in Biomedical Research and Healthcare
Ernesto Díaz-Flores, Tim Meyer, Alexis Giorkallos
Advances in biochemical engineering, biotechnology (2022), pp. 23-60
Closed Access | Times Cited: 16
Reducing false positive rate of docking-based virtual screening by active learning
Lei Wang, Shaohua Shi, Hui Li, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 1
Closed Access | Times Cited: 8
Enhancing Generalizability in Protein–Ligand Binding Affinity Prediction with Multimodal Contrastive Learning
Ding Luo, Dandan Liu, Xiaoyang Qu, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 6, pp. 1892-1906
Closed Access | Times Cited: 2
Machine learning-based virtual screening of multi-target anti-obesity compounds from medicinal and edible plants: A combined in silico and in vitro study
Xincheng Zhou, Jian Ni, Weiben Ge, et al.
Food Bioscience (2024) Vol. 59, pp. 104077-104077
Closed Access | Times Cited: 2
Perspectives on current approaches to virtual screening in drug discovery
Ingo Muegge, Jörg Bentzien, Ge Yunhui
Expert Opinion on Drug Discovery (2024) Vol. 19, Iss. 10, pp. 1173-1183
Closed Access | Times Cited: 2
Library size in virtual screening: is it truly a number’s game?
Maria Kontoyianni
Expert Opinion on Drug Discovery (2022) Vol. 17, Iss. 11, pp. 1177-1179
Closed Access | Times Cited: 11
OptNCMiner: a deep learning approach for the discovery of natural compounds modulating disease-specific multi-targets
Seo Hyun Shin, Seung Man Oh, Jung Han Yoon Park, et al.
BMC Bioinformatics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 10
Advances in machine intelligence‐driven virtual screening approaches for big‐data
Neeraj Kumar, Vishal Acharya
Medicinal Research Reviews (2023) Vol. 44, Iss. 3, pp. 939-974
Closed Access | Times Cited: 5
ClassyPose: A Machine‐Learning Classification Model for Ligand Pose Selection Applied to Virtual Screening in Drug Discovery
Viet‐Khoa Tran‐Nguyen, Anne‐Claude Camproux, Olivier Taboureau
Advanced Intelligent Systems (2024) Vol. 6, Iss. 12
Open Access | Times Cited: 1
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