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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:

High-throughput virtual laboratory for drug discovery using massive datasets
Jens Gläser, Josh V. Vermaas, David Rogers, et al.
The International Journal of High Performance Computing Applications (2021) Vol. 35, Iss. 5, pp. 452-468
Closed Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

A Review on Parallel Virtual Screening Softwares for High-Performance Computers
N. Arul Murugan, Artur Podobas, Davide Gadioli, et al.
Pharmaceuticals (2022) Vol. 15, Iss. 1, pp. 63-63
Open Access | Times Cited: 47
Comprehensive Survey of Consensus Docking for High-Throughput Virtual Screening
Clara Blanes‐Mira, Pilar Fernández-Aguado, Jorge de Andrés-López, et al.
Molecules (2022) Vol. 28, Iss. 1, pp. 175-175
Open Access | Times Cited: 41
Uni-Dock: GPU-Accelerated Docking Enables Ultralarge Virtual Screening
Yuejiang Yu, Chun Cai, Jiayue Wang, et al.
Journal of Chemical Theory and Computation (2023) Vol. 19, Iss. 11, pp. 3336-3345
Closed Access | Times Cited: 37
EspalomaCharge: Machine Learning-Enabled Ultrafast Partial Charge Assignment
Yuanqing Wang, Iván Pulido, Kenichiro Takaba, et al.
The Journal of Physical Chemistry A (2024) Vol. 128, Iss. 20, pp. 4160-4167
Open Access | Times Cited: 12
High performance-oriented computer aided drug design approaches in the exascale era
Andrea Rizzi, Davide Mandelli
Expert Opinion on Drug Discovery (2025)
Closed Access
Fully automated high-throughput computer-based catalytic material screening framework and its application on the new-generation Tianhe supercomputer
Can Leng, Xuguang Chen, Jie Liu, et al.
Computational Materials Science (2025) Vol. 252, pp. 113775-113775
Closed Access
SARS-CoV2 billion-compound docking
David Rogers, Rupesh Agarwal, Josh V. Vermaas, et al.
Scientific Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 14
GPU-optimized approaches to molecular docking-based virtual screening in drug discovery: A comparative analysis
Emanuele Vitali, Federico Ficarelli, Mauro Bisson, et al.
Journal of Parallel and Distributed Computing (2023) Vol. 186, pp. 104819-104819
Open Access | Times Cited: 10
Out of kernel tuning and optimizations for portable large-scale docking experiments on GPUs
Gianmarco Accordi, Davide Gadioli, Emanele Vitali, et al.
The Journal of Supercomputing (2024) Vol. 80, Iss. 8, pp. 11798-11815
Open Access | Times Cited: 3
EXSCALATE: An Extreme-Scale Virtual Screening Platform for Drug Discovery Targeting Polypharmacology to Fight SARS-CoV-2
Davide Gadioli, Emanuele Vitali, Federico Ficarelli, et al.
IEEE Transactions on Emerging Topics in Computing (2022) Vol. 11, Iss. 1, pp. 170-181
Open Access | Times Cited: 17
Evaluating Scalable Supervised Learning for Synthesize-on-Demand Chemical Libraries
Moayad Alnammi, Shengchao Liu, Spencer S. Ericksen, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 17, pp. 5513-5528
Open Access | Times Cited: 9
EspalomaCharge: Machine learning-enabled ultra-fast partial charge assignment
Yuanqing Wang, Iván Pulido, Kenichiro Takaba, et al.
arXiv (Cornell University) (2023)
Open Access | Times Cited: 8
Machine learning in metastatic cancer research: Potentials, possibilities, and prospects
Olutomilayo Olayemi Petinrin, Faisal Saeed, Muhammad Toseef, et al.
Computational and Structural Biotechnology Journal (2023) Vol. 21, pp. 2454-2470
Open Access | Times Cited: 8
DENVIS: Scalable and High-Throughput Virtual Screening Using Graph Neural Networks with Atomic and Surface Protein Pocket Features
Agamemnon Krasoulis, Nick Antonopoulos, Vassilis Pitsikalis, et al.
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 19, pp. 4642-4659
Open Access | Times Cited: 12
Scalable HPC & AI infrastructure for COVID-19 therapeutics
Hyungro Lee, André Merzky, Li Lynn Tan, et al.
(2021), pp. 1-13
Open Access | Times Cited: 16
Coupling streaming AI and HPC ensembles to achieve 100–1000× faster biomolecular simulations
Alexander Brace, Igor Yakushin, Heng Ma, et al.
2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS) (2022)
Open Access | Times Cited: 11
Drugging the entire human proteome: Are we there yet?
Micholas Dean Smith, L. Darryl Quarles, Omar Demerdash, et al.
Drug Discovery Today (2024) Vol. 29, Iss. 3, pp. 103891-103891
Open Access | Times Cited: 1
MDFit: Automated molecular simulations workflow enables high throughput assessment of ligands-protein dynamics
Alexander C. Brueckner, Benjamin Shields, Palani Kirubakaran, et al.
(2024)
Open Access | Times Cited: 1
LS-HTC: an HTC system for large-scale jobs
Juncheng Hu, Xilong Che, Bowen Kan, et al.
CCF Transactions on High Performance Computing (2024) Vol. 6, Iss. 3, pp. 301-318
Closed Access | Times Cited: 1
Enabling performance portability on the LiGen drug discovery pipeline
Luigi Crisci, Lorenzo Carpentieri, Biagio Cosenza, et al.
Future Generation Computer Systems (2024) Vol. 158, pp. 44-59
Open Access | Times Cited: 1
MDFit: automated molecular simulations workflow enables high throughput assessment of ligands-protein dynamics
Alexander C. Brueckner, Benjamin Shields, Palani Kirubakaran, et al.
Journal of Computer-Aided Molecular Design (2024) Vol. 38, Iss. 1
Closed Access | Times Cited: 1
FP-MAP: an extensive library of fingerprint-based molecular activity prediction tools
Vishwesh Venkatraman
Frontiers in Chemistry (2023) Vol. 11
Open Access | Times Cited: 4
TwoFold: Highly accurate structure and affinity prediction for protein-ligand complexes from sequences
Darren J. Hsu, Hao Lu, Aditya Kashi, et al.
The International Journal of High Performance Computing Applications (2023) Vol. 37, Iss. 6, pp. 666-682
Closed Access | Times Cited: 4
Achieving 100X faster simulations of complex biological phenomena by coupling ML to HPC ensembles.
Alexander Brace, Hyungro Lee, Heng Ma, et al.
arXiv (Cornell University) (2021)
Closed Access | Times Cited: 9
Portability for GPU-accelerated molecular docking applications for cloud and HPC: can portable compiler directives provide performance across all platforms?
Mathialakan Thavappiragasam, Wael Elwasif, Ada Sedova
2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid) (2022), pp. 975-984
Open Access | Times Cited: 4
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