Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

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

Showing 1-25 of 141 citing articles:

Artificial intelligence in drug discovery: recent advances and future perspectives
José Jiménez-Luna, Francesca Grisoni, Nils Weskamp, et al.
Expert Opinion on Drug Discovery (2021) Vol. 16, Iss. 9, pp. 949-959
Open Access | Times Cited: 274
Deep Learning in Virtual Screening: Recent Applications and Developments
Talia B. Kimber, Yonghui Chen, Andrea Volkamer
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 9, pp. 4435-4435
Open Access | Times Cited: 154
AI in drug discovery and its clinical relevance
Rizwan Qureshi, Muhammad Irfan, Taimoor Muzaffar Gondal, et al.
Heliyon (2023) Vol. 9, Iss. 7, pp. e17575-e17575
Open Access | Times Cited: 124
A geometric deep learning approach to predict binding conformations of bioactive molecules
Oscar Méndez‐Lucio, Mazen Ahmad, Ehecatl Antonio del Rio‐Chanona, et al.
Nature Machine Intelligence (2021) Vol. 3, Iss. 12, pp. 1033-1039
Closed Access | Times Cited: 123
Boosting Protein–Ligand Binding Pose Prediction and Virtual Screening Based on Residue–Atom Distance Likelihood Potential and Graph Transformer
Chao Shen, Xujun Zhang, Yafeng Deng, et al.
Journal of Medicinal Chemistry (2022) Vol. 65, Iss. 15, pp. 10691-10706
Closed Access | Times Cited: 103
Protein–Ligand Docking in the Machine-Learning Era
Chao Yang, Eric Anthony Chen, Yingkai Zhang
Molecules (2022) Vol. 27, Iss. 14, pp. 4568-4568
Open Access | Times Cited: 75
Scoring Functions for Protein-Ligand Binding Affinity Prediction Using Structure-based Deep Learning: A Review
Rocco Meli, Garrett M. Morris, Philip C. Biggin
Frontiers in Bioinformatics (2022) Vol. 2
Open Access | Times Cited: 70
New avenues in artificial-intelligence-assisted drug discovery
Carmen Cerchia, Antonio Lavecchia
Drug Discovery Today (2023) Vol. 28, Iss. 4, pp. 103516-103516
Open Access | Times Cited: 52
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
Enhancing preclinical drug discovery with artificial intelligence
Ramachandran Vijayan, Jan Kihlberg, Jason B. Cross, et al.
Drug Discovery Today (2021) Vol. 27, Iss. 4, pp. 967-984
Open Access | Times Cited: 94
AK-Score: Accurate Protein-Ligand Binding Affinity Prediction Using an Ensemble of 3D-Convolutional Neural Networks
Yongbeom Kwon, Woong‐Hee Shin, Junsu Ko, et al.
International Journal of Molecular Sciences (2020) Vol. 21, Iss. 22, pp. 8424-8424
Open Access | Times Cited: 87
Property-Unmatched Decoys in Docking Benchmarks
Reed M. Stein, Yang Ying, Trent E. Balius, et al.
Journal of Chemical Information and Modeling (2021) Vol. 61, Iss. 2, pp. 699-714
Open Access | Times Cited: 86
Applications of Virtual Screening in Bioprospecting: Facts, Shifts, and Perspectives to Explore the Chemo-Structural Diversity of Natural Products
Kauȇ Santana da Costa, Lidiane Diniz do Nascimento, Anderson Lima e Lima, et al.
Frontiers in Chemistry (2021) Vol. 9
Open Access | Times Cited: 62
Generating property-matched decoy molecules using deep learning
Fergus Imrie, A.R. Bradley, Charlotte M. Deane
Bioinformatics (2021) Vol. 37, Iss. 15, pp. 2134-2141
Open Access | Times Cited: 59
DrugRep: an automatic virtual screening server for drug repurposing
Jianhong Gan, Jixiang Liu, Yang Liu, et al.
Acta Pharmacologica Sinica (2022) Vol. 44, Iss. 4, pp. 888-896
Open Access | Times Cited: 59
Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2
Kaifu Gao, Rui Wang, Jiahui Chen, et al.
Chemical Reviews (2022) Vol. 122, Iss. 13, pp. 11287-11368
Open Access | Times Cited: 53
A point cloud-based deep learning strategy for protein–ligand binding affinity prediction
Yeji Wang, Shuo Wu, Yanwen Duan, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Open Access | Times Cited: 53
DOCKSTRING: Easy Molecular Docking Yields Better Benchmarks for Ligand Design
Miguel García-Ortegón, Gregor N. C. Simm, Austin Tripp, et al.
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 15, pp. 3486-3502
Open Access | Times Cited: 51
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
A fully differentiable ligand pose optimization framework guided by deep learning and a traditional scoring function
Zechen Wang, Liangzhen Zheng, Sheng Wang, et al.
Briefings in Bioinformatics (2022) Vol. 24, Iss. 1
Open Access | Times Cited: 35
Simple nearest-neighbour analysis meets the accuracy of compound potency predictions using complex machine learning models
Tiago Janela, Jürgen Bajorath
Nature Machine Intelligence (2022) Vol. 4, Iss. 12, pp. 1246-1255
Closed Access | Times Cited: 35
Converting Nanotoxicity Data to Information Using Artificial Intelligence and Simulation
Xiliang Yan, Tongtao Yue, David A. Winkler, et al.
Chemical Reviews (2023) Vol. 123, Iss. 13, pp. 8575-8637
Closed Access | Times Cited: 29
Open-Source Machine Learning in Computational Chemistry
Alexander Hagg, Karl N. Kirschner
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 15, pp. 4505-4532
Open Access | Times Cited: 23
Integrated Molecular Modeling and Machine Learning for Drug Design
Song Xia, Eric Chen, Yingkai Zhang
Journal of Chemical Theory and Computation (2023) Vol. 19, Iss. 21, pp. 7478-7495
Open Access | Times Cited: 23
Learning characteristics of graph neural networks predicting protein–ligand affinities
Andrea Mastropietro, Giuseppe Pasculli, Jürgen Bajorath
Nature Machine Intelligence (2023) Vol. 5, Iss. 12, pp. 1427-1436
Closed Access | Times Cited: 23
Page 1 - Next Page

Scroll to top