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:

D3R Grand Challenge 4: prospective pose prediction of BACE1 ligands with AutoDock-GPU
Diogo Santos‐Martins, Jérôme Eberhardt, Giulia Bianco, et al.
Journal of Computer-Aided Molecular Design (2019) Vol. 33, Iss. 12, pp. 1071-1081
Open Access | Times Cited: 33

Showing 1-25 of 33 citing articles:

AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings
Jérôme Eberhardt, Diogo Santos‐Martins, Andreas F. Tillack, et al.
Journal of Chemical Information and Modeling (2021) Vol. 61, Iss. 8, pp. 3891-3898
Open Access | Times Cited: 3070

Accelerating AutoDock4 with GPUs and Gradient-Based Local Search
Diogo Santos‐Martins, Leonardo Solis-Vasquez, Andreas F. Tillack, et al.
Journal of Chemical Theory and Computation (2021) Vol. 17, Iss. 2, pp. 1060-1073
Open Access | Times Cited: 239

TheAutoDocksuite at 30
David S. Goodsell, Michel F. Sanner, Arthur J. Olson, et al.
Protein Science (2020) Vol. 30, Iss. 1, pp. 31-43
Open Access | Times Cited: 146

AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings
Jérôme Eberhardt, Diogo Santos‐Martins, Andreas F. Tillack, et al.
(2021)
Open Access | Times Cited: 140

Accelerating AutoDock Vina with GPUs
Shidi Tang, Ruiqi Chen, Mengru Lin, et al.
Molecules (2022) Vol. 27, Iss. 9, pp. 3041-3041
Open Access | Times Cited: 65

AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings
Jérôme Eberhardt, Diogo Santos‐Martins, Andreas F. Tillack, et al.
(2021)
Open Access | Times Cited: 56

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

GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer
Scott LeGrand, Aaron Scheinberg, Andreas F. Tillack, et al.
(2020), pp. 1-10
Open Access | Times Cited: 44

Benchmarking the performance of irregular computations in AutoDock-GPU molecular docking
Leonardo Solis-Vasquez, Andreas F. Tillack, Diogo Santos‐Martins, et al.
Parallel Computing (2021) Vol. 109, pp. 102861-102861
Open Access | Times Cited: 26

Supercomputing Pipelines Search for Therapeutics Against COVID-19
Josh V. Vermaas, Ada Sedova, Matthew Baker, et al.
Computing in Science & Engineering (2020) Vol. 23, Iss. 1, pp. 7-16
Open Access | Times Cited: 26

The role of artificial intelligence in drug screening, drug design, and clinical trials
Yaojiong Wu, Li Ma, Xinyi Li, et al.
Frontiers in Pharmacology (2024) Vol. 15
Open Access | Times Cited: 2

GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer: Porting, Optimization, and Application to COVID-19 Research.
Scott LeGrand, Aaron Scheinberg, Andreas F. Tillack, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 19

Performance evaluation of flexible macrocycle docking in AutoDock
Matthew Holcomb, Diogo Santos‐Martins, Andreas F. Tillack, et al.
QRB Discovery (2022) Vol. 3
Open Access | Times Cited: 9

Recent breakthroughs in computational structural biology harnessing the power of sequences and structures
Bálint Mészáros, Electa Park, Duccio Malinverni, et al.
Current Opinion in Structural Biology (2023) Vol. 80, pp. 102608-102608
Open Access | Times Cited: 4

GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer: Porting, Optimization, and Application to COVID-19 Research.
Scott LeGrand, Aaron Scheinberg, Andreas F. Tillack, et al.
PubMed (2020)
Open Access | Times Cited: 11

iORandLigandDB: A Website for Three-Dimensional Structure Prediction of Insect Odorant Receptors and Docking with Odorants
Shuo Jin, Kun Qian, Lin He, et al.
Insects (2023) Vol. 14, Iss. 6, pp. 560-560
Open Access | Times Cited: 2

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

Performance Portability of Molecular Docking Miniapp On Leadership Computing Platforms
Mathialakan Thavappiragasam, Aaron Scheinberg, Wael Elwasif, et al.
(2020)
Open Access | Times Cited: 5

Perspective on the SAMPL and D3R Blind Prediction Challenges for Physics-Based Free Energy Methods
Nicolas Tielker, Lukas Eberlein, Oliver Beckstein, et al.
ACS symposium series (2021), pp. 67-107
Open Access | Times Cited: 5

Accelerating AutoDock VINA with GPUs
Shidi Tang, Ruiqi Chen, Lin Mengru, et al.
(2021)
Open Access | Times Cited: 4

Reactive Docking: a computational method for high-throughput virtual screenings of reactive species
Giulia Bianco, Matthew Holcomb, Diogo Santos‐Martins, et al.
(2023)
Open Access | Times Cited: 1

Reactive Docking: A Computational Method for High-Throughput Virtual Screenings of Reactive Species
Giulia Bianco, Matthew Holcomb, Diogo Santos‐Martins, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 17, pp. 5631-5640
Open Access | Times Cited: 1

Accelerating AutoDock VINA with GPUs
Shidi Tang, Ruiqi Chen, Lin Mengru, et al.
(2022)
Closed Access | Times Cited: 2

Accelerating AutoDock VINA with GPUs
Shidi Tang, Ruiqi Chen, Lin Mengru, et al.
(2022)
Open Access | Times Cited: 2

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