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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:

Machine learning coarse-grained potentials of protein thermodynamics
Maciej Majewski, Adrià Pérez, Philipp Thölke, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 56

Showing 1-25 of 56 citing articles:

Pragmatic Coarse-Graining of Proteins: Models and Applications
Luís Borges-Araújo, Ilias Patmanidis, Akhil Pratap Singh, et al.
Journal of Chemical Theory and Computation (2023) Vol. 19, Iss. 20, pp. 7112-7135
Open Access | Times Cited: 48
Integrating cellular electron microscopy with multimodal data to explore biology across space and time
Caitlyn L McCafferty, Sven Klumpe, Rommie E. Amaro, et al.
Cell (2024) Vol. 187, Iss. 3, pp. 563-584
Open Access | Times Cited: 41
TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations
Raúl P. Peláez, Guillem Simeon, Raimondas Galvelis, et al.
Journal of Chemical Theory and Computation (2024) Vol. 20, Iss. 10, pp. 4076-4087
Open Access | Times Cited: 16
The Potential of Neural Network Potentials
Timothy T. Duignan
ACS Physical Chemistry Au (2024) Vol. 4, Iss. 3, pp. 232-241
Open Access | Times Cited: 14
In Silico Chemical Experiments in the Age of AI: From Quantum Chemistry to Machine Learning and Back
Abdulrahman Aldossary, Jorge A. Campos-Gonzalez-Angulo, Sergio Pablo‐García, et al.
Advanced Materials (2024) Vol. 36, Iss. 30
Closed Access | Times Cited: 13
A Perspective on Protein Structure Prediction Using Quantum Computers
Hakan Doğa, Bryan Raubenolt, Fabio Cumbo, et al.
Journal of Chemical Theory and Computation (2024) Vol. 20, Iss. 9, pp. 3359-3378
Open Access | Times Cited: 11
Transferable deep generative modeling of intrinsically disordered protein conformations
Giacomo Janson, Michael Feig
PLoS Computational Biology (2024) Vol. 20, Iss. 5, pp. e1012144-e1012144
Open Access | Times Cited: 11
FlowBack: A Generalized Flow-Matching Approach for Biomolecular Backmapping
Michael S. Jones, Smayan Khanna, Andrew L. Ferguson
Journal of Chemical Information and Modeling (2025)
Closed Access | Times Cited: 1
The Physics-AI Dialogue in Drug Design
Pablo Andrés Vargas-Rosales, Amedeo Caflisch
RSC Medicinal Chemistry (2025)
Open Access | Times Cited: 1
Scaling Graph Neural Networks to Large Proteins
Justin Airas, Bin Zhang
Journal of Chemical Theory and Computation (2025)
Open Access | Times Cited: 1
Deep generative modeling of temperature-dependent structural ensembles of proteins
Giacomo Janson, Alexander Jussupow, Michael Feig
bioRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access | Times Cited: 1
Global ranking of the sensitivity of interaction potential contributions within classical molecular dynamics force fields
Wouter Edeling, Maxime Vassaux, Yiming Yang, et al.
npj Computational Materials (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 6
Transferable Implicit Solvation via Contrastive Learning of Graph Neural Networks
Justin Airas, Xinqiang Ding, Bin Zhang
ACS Central Science (2023) Vol. 9, Iss. 12, pp. 2286-2297
Open Access | Times Cited: 14
A cyclical route linking fundamental mechanism and AI algorithm: An example from tuning Poisson's ratio in amorphous networks
Changliang Zhu, Chenchao Fang, Zhipeng Jin, et al.
Applied Physics Reviews (2024) Vol. 11, Iss. 3
Open Access | Times Cited: 5
pLDDT Values in AlphaFold2 Protein Models Are Unrelated to Globular Protein Local Flexibility
Oliviero Carugo
Crystals (2023) Vol. 13, Iss. 11, pp. 1560-1560
Open Access | Times Cited: 12
DiAMoNDBack: Diffusion-Denoising Autoregressive Model for Non-Deterministic Backmapping of Cα Protein Traces
Michael S. Jones, Kirill Shmilovich, Andrew L. Ferguson
Journal of Chemical Theory and Computation (2023) Vol. 19, Iss. 21, pp. 7908-7923
Closed Access | Times Cited: 11
Transferable deep generative modeling of intrinsically disordered protein conformations
Giacomo Janson, Michael Feig
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 4
Utilizing Molecular Dynamics Simulations, Machine Learning, Cryo-EM, and NMR Spectroscopy to Predict and Validate Protein Dynamics
Ahrum Son, Woojin Kim, Jongham Park, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 17, pp. 9725-9725
Open Access | Times Cited: 4
Computational protein design
Katherine I. Albanese, Sophie Barbe, Derek N. Woolfson, et al.
Nature Reviews Methods Primers (2025) Vol. 5, Iss. 1
Open Access
On the emergence of machine-learning methods in bottom-up coarse-graining
Patrick G. Sahrmann, Gregory A. Voth
Current Opinion in Structural Biology (2025) Vol. 90, pp. 102972-102972
Closed Access
Editorial: Revolutionizing life sciences: the nobel leap in artificial intelligence-driven biomodeling
Valentina Tozzini, Cecilia Giulivi
Frontiers in Molecular Biosciences (2025) Vol. 11
Open Access
A Neural-Network-Based Mapping and Optimization Framework for High-Precision Coarse-Grained Simulation
Zhixuan Zhong, Lifeng Xu, Jian Jiang
Journal of Chemical Theory and Computation (2025)
Open Access
Machine learning in molecular biophysics: Protein allostery, multi-level free energy simulations, and lipid phase transitions
Qiang Cui
Biophysics Reviews (2025) Vol. 6, Iss. 1
Closed Access
Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning
Talant Ruzmetov, Ta I Hung, Saisri Padmaja Jonnalagedda, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access
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