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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 approach for accurate backmapping of coarse-grained models to all-atom models
Yaxin An, Sanket A. Deshmukh
Chemical Communications (2020) Vol. 56, Iss. 65, pp. 9312-9315
Closed Access | Times Cited: 49

Showing 1-25 of 49 citing articles:

Polymer informatics: Current status and critical next steps
Lihua Chen, Ghanshyam Pilania, Rohit Batra, et al.
Materials Science and Engineering R Reports (2020) Vol. 144, pp. 100595-100595
Open Access | Times Cited: 217
A review of advancements in coarse-grained molecular dynamics simulations
Soumil Y. Joshi, Sanket A. Deshmukh
Molecular Simulation (2020) Vol. 47, Iss. 10-11, pp. 786-803
Open Access | Times Cited: 198
Bottom-up Coarse-Graining: Principles and Perspectives
Jaehyeok Jin, Alexander J. Pak, Aleksander E. P. Durumeric, et al.
Journal of Chemical Theory and Computation (2022) Vol. 18, Iss. 10, pp. 5759-5791
Open Access | Times Cited: 171
CG2AT2: an Enhanced Fragment-Based Approach for Serial Multi-scale Molecular Dynamics Simulations
Owen N. Vickery, Phillip J. Stansfeld
Journal of Chemical Theory and Computation (2021) Vol. 17, Iss. 10, pp. 6472-6482
Open Access | Times Cited: 109
Perspective: Advances, Challenges, and Insight for Predictive Coarse-Grained Models
W. G. Noid
The Journal of Physical Chemistry B (2023) Vol. 127, Iss. 19, pp. 4174-4207
Open Access | Times Cited: 80
Approximating Projections of Conformational Boltzmann Distributions with AlphaFold2 Predictions: Opportunities and Limitations
Benjamin P. Brown, Richard A. Stein, Jens Meiler, et al.
Journal of Chemical Theory and Computation (2024) Vol. 20, Iss. 3, pp. 1434-1447
Open Access | Times Cited: 19
Comparative Analysis of Machine Learning Models for Crop Yield Prediction Across Multiple Crop Types
Y.M. Patil, R Harikrishnan, S. Sundararajan, et al.
SN Computer Science (2025) Vol. 6, Iss. 1
Closed Access | Times Cited: 2
Chemically specific coarse‐graining of polymers: Methods and prospects
Satyen Dhamankar, Michael Webb
Journal of Polymer Science (2021) Vol. 59, Iss. 22, pp. 2613-2643
Open Access | Times Cited: 94
Coarse-grained modelling out of equilibrium
Tanja Schilling
Physics Reports (2022) Vol. 972, pp. 1-45
Open Access | Times Cited: 63
Machine Learning in Soft Matter: From Simulations to Experiments
Kaihua Zhang, Xiangrui Gong, Ying Jiang
Advanced Functional Materials (2024) Vol. 34, Iss. 24
Closed Access | Times Cited: 9
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
A review of computational studies of bottlebrush polymers
Esmat Mohammadi, Soumil Y. Joshi, Sanket A. Deshmukh
Computational Materials Science (2021) Vol. 199, pp. 110720-110720
Open Access | Times Cited: 42
Integrating Machine Learning in the Coarse-Grained Molecular Simulation of Polymers
Eleonora Ricci, Niki Vergadou
The Journal of Physical Chemistry B (2023) Vol. 127, Iss. 11, pp. 2302-2322
Closed Access | Times Cited: 16
Bringing Quantum Mechanics to Coarse-Grained Soft Materials Modeling
Chun-I Wang, Nicholas E. Jackson
Chemistry of Materials (2023) Vol. 35, Iss. 4, pp. 1470-1486
Closed Access | Times Cited: 15
The confluence of machine learning and multiscale simulations
Harsh Bhatia, Fikret Aydin, Timothy S. Carpenter, et al.
Current Opinion in Structural Biology (2023) Vol. 80, pp. 102569-102569
Open Access | Times Cited: 14
GLIMPS: A Machine Learning Approach to Resolution Transformation for Multiscale Modeling
Keverne A. Louison, Ian L. Dryden, Charles A. Laughton
Journal of Chemical Theory and Computation (2021) Vol. 17, Iss. 12, pp. 7930-7937
Open Access | Times Cited: 31
Coarse-Grained Density Functional Theory Predictions via Deep Kernel Learning
Ganesh Sivaraman, Nicholas E. Jackson
Journal of Chemical Theory and Computation (2022) Vol. 18, Iss. 2, pp. 1129-1141
Open Access | Times Cited: 21
Bypassing backmapping: Coarse-grained electronic property distributions using heteroscedastic Gaussian processes
J. Charlie Maier, Nicholas E. Jackson
The Journal of Chemical Physics (2022) Vol. 157, Iss. 17
Closed Access | Times Cited: 20
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
Structural Coarse-Graining via Multiobjective Optimization with Differentiable Simulation
Zhenghao Wu, Tianhang Zhou
Journal of Chemical Theory and Computation (2024) Vol. 20, Iss. 6, pp. 2605-2617
Closed Access | Times Cited: 4
ART-SM: Boosting Fragment-Based Backmapping by Machine Learning
Christian Pfaendner, Viktoria Korn, Pritom Gogoi, et al.
Journal of Chemical Theory and Computation (2025)
Closed Access
Distilling coarse-grained representations of molecular electronic structure with continuously gated message passing
J. Charlie Maier, Chun-I Wang, Nicholas E. Jackson
The Journal of Chemical Physics (2024) Vol. 160, Iss. 2
Open Access | Times Cited: 3
Asynchronous Reciprocal Coupling of Martini 2.2 Coarse-Grained and CHARMM36 All-Atom Simulations in an Automated Multiscale Framework
César A. López, Xiaohua Zhang, Fikret Aydin, et al.
Journal of Chemical Theory and Computation (2022) Vol. 18, Iss. 8, pp. 5025-5045
Open Access | Times Cited: 14
Physics-Informed Deep Learning Approach for Reintroducing Atomic Detail in Coarse-Grained Configurations of Multiple Poly(lactic acid) Stereoisomers
Eleftherios Christofi, Petra Bačová, Vagelis Harmandaris
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 6, pp. 1853-1867
Open Access | Times Cited: 2
Self-Optimizing Bayesian for Continuous Flow Synthesis Process
Runzhe Liu, Zihao Wang, Wenbo Yang, et al.
Digital Discovery (2024)
Open Access | Times Cited: 2
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