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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:

SCONES: Self-Consistent Neural Network for Protein Stability Prediction Upon Mutation
Yashas B. L. Samaga, Shampa Raghunathan, U. Deva Priyakumar
The Journal of Physical Chemistry B (2021) Vol. 125, Iss. 38, pp. 10657-10671
Closed Access | Times Cited: 25

Showing 25 citing articles:

Artificial intelligence: machine learning for chemical sciences
A. Karthikeyan, U. Deva Priyakumar
Journal of Chemical Sciences (2021) Vol. 134, Iss. 1
Open Access | Times Cited: 58
PROSTATA: a framework for protein stability assessment using transformers
Dmitriy Umerenkov, Fedor Nikolaev, Tatiana Shashkova, et al.
Bioinformatics (2023) Vol. 39, Iss. 11
Open Access | Times Cited: 19
Modern machine learning methods for protein property prediction
Arjun Dosajh, P. K. Agrawal, Prathit Chatterjee, et al.
Current Opinion in Structural Biology (2025) Vol. 90, pp. 102990-102990
Closed Access
Molecular representations for machine learning applications in chemistry
Shampa Raghunathan, U. Deva Priyakumar
International Journal of Quantum Chemistry (2021) Vol. 122, Iss. 7
Open Access | Times Cited: 48
Recent Advances in Machine Learning Variant Effect Prediction Tools for Protein Engineering
Jesse Horne, Diwakar Shukla
Industrial & Engineering Chemistry Research (2022) Vol. 61, Iss. 19, pp. 6235-6245
Open Access | Times Cited: 31
Developability assessment at early-stage discovery to enable development of antibody-derived therapeutics
Weijie Zhang, Hao Wang, Nan Feng, et al.
Antibody Therapeutics (2022) Vol. 6, Iss. 1, pp. 13-29
Open Access | Times Cited: 26
Accelerating therapeutic protein design with computational approaches toward the clinical stage
Zhidong Chen, Xinpei Wang, Xu Chen, et al.
Computational and Structural Biotechnology Journal (2023) Vol. 21, pp. 2909-2926
Open Access | Times Cited: 16
Challenges in predicting stabilizing variations: An exploration
Silvia Benevenuta, Giovanni Birolo, Tiziana Sanavia, et al.
Frontiers in Molecular Biosciences (2023) Vol. 9
Open Access | Times Cited: 11
DeepSPInN – deep reinforcement learning for molecular structure prediction from infrared and 13C NMR spectra
Sriram Devata, Bhuvanesh Sridharan, Sarvesh Mehta, et al.
Digital Discovery (2024) Vol. 3, Iss. 4, pp. 818-829
Open Access | Times Cited: 3
MEMES: Machine learning framework for Enhanced MolEcular Screening
Sarvesh Mehta, Siddhartha Laghuvarapu, Yashaswi Pathak, et al.
Chemical Science (2021) Vol. 12, Iss. 35, pp. 11710-11721
Open Access | Times Cited: 29
Computational Advances in Protein Engineering and Enzyme Design
Étienne Derat, Shina Caroline Lynn Kamerlin
The Journal of Physical Chemistry B (2022) Vol. 126, Iss. 13, pp. 2449-2451
Closed Access | Times Cited: 17
Modern computational methods for rational enzyme engineering
Pedro Ferreira, Pedro Alexandrino Fernandes, Maria J. Ramos
Chem Catalysis (2022) Vol. 2, Iss. 10, pp. 2481-2498
Open Access | Times Cited: 16
Predicting protein thermal stability changes upon single and multi-point mutations via restricted attention subgraph neural network
Mohammad Madani, Anna Tarakanova
Journal of the Mechanics and Physics of Solids (2024) Vol. 184, pp. 105531-105531
Closed Access | Times Cited: 2
DeepSPInN - Deep reinforcement learning for molecular Structure Prediction from Infrared and 13C NMR spectra
Sriram Devata, Bhuvanesh Sridharan, Sarvesh Mehta, et al.
(2024)
Open Access | Times Cited: 2
Efficient and feasible biocatalysts: Strategies for enzyme improvement. A review
Samah Hashim Albayati, Nima Ghahremani Nezhad, Abdulrahman M Taki, et al.
International Journal of Biological Macromolecules (2024) Vol. 276, pp. 133978-133978
Closed Access | Times Cited: 2
TorRNA - Improved Prediction of Backbone Torsion Angles of RNA by Leveraging Large Language Models
Sriram Devata, Deva Priyakumar U.
(2024)
Open Access | Times Cited: 1
PROSTATA: Protein Stability Assessment using Transformers
Dmitriy Umerenkov, Tatiana Shashkova, П. В. Страшнов, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 7
Using genetic programming to predict and optimize protein function
Iliya Miralavy, Alexander R. Bricco, Assaf A. Gilad, et al.
PeerJ Physical Chemistry (2022) Vol. 4, pp. e24-e24
Open Access | Times Cited: 6
CalFitter 2.0: Leveraging the power of singular value decomposition to analyse protein thermostability
Antonín Kunka, David Lacko, Jan Štourač, et al.
Nucleic Acids Research (2022) Vol. 50, Iss. W1, pp. W145-W151
Open Access | Times Cited: 4
Recent Advances in the Integration of Protein Mechanics and Machine Learning
Yen‐Lin Chen, Shu‐Wei Chang
Extreme Mechanics Letters (2024), pp. 102236-102236
Closed Access
AI Prediction of Structural Stability of Nanoproteins Based on Structures and Residue Properties by Mean Pooled Dual Graph Convolutional Network
Daixi Li, Yuqi Zhu, Wujie Zhang, et al.
Interdisciplinary Sciences Computational Life Sciences (2024)
Closed Access
DeepSPInN - multimodal Deep learning for molecular Structure Prediction from Infrared and NMR spectra
Sriram Devata, Bhuvanesh Sridharan, Sarvesh Mehta, et al.
(2023)
Open Access | Times Cited: 1
Construction of Mitochondrial Protection and Monitoring Model of Lon Protease Based on Machine Learning under Myocardial Ischemia Environment
Jinliang Wang, Yang Zhang, Haijiao Shi, et al.
Journal of Environmental and Public Health (2022) Vol. 2022, Iss. 1
Open Access | Times Cited: 1
FOMO: A Fragment-based Objective Molecule Optimization Framework
Cong Ma, Zeqi Zhang, Min Xu, et al.
Research Square (Research Square) (2023)
Open Access
Peer Review #2 of "Using genetic programming to predict and optimize protein function (v0.1)"

(2022)
Open Access
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