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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:

Novel Solubility Prediction Models: Molecular Fingerprints and Physicochemical Features vs Graph Convolutional Neural Networks
Sumin Lee, Myeonghun Lee, Ki-Won Gyak, et al.
ACS Omega (2022) Vol. 7, Iss. 14, pp. 12268-12277
Open Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

MolToxPred: small molecule toxicity prediction using machine learning approach
Anjali Setiya, Vinod Jani, Uddhavesh Sonavane, et al.
RSC Advances (2024) Vol. 14, Iss. 6, pp. 4201-4220
Open Access | Times Cited: 9
The Artificial Intelligence-Powered New Era in Pharmaceutical Research and Development: A Review
Phuvamin Suriyaamporn, Boonnada Pamornpathomkul, Prasopchai Patrojanasophon, et al.
AAPS PharmSciTech (2024) Vol. 25, Iss. 6
Closed Access | Times Cited: 7
MolFPG: Multi-level fingerprint-based Graph Transformer for accurate and robust drug toxicity prediction
Saisai Teng, Chenglin Yin, Yu Wang, et al.
Computers in Biology and Medicine (2023) Vol. 164, pp. 106904-106904
Closed Access | Times Cited: 20
When Machine Learning and Deep Learning Come to the Big Data in Food Chemistry
Yufeng Jane Tseng, Pei-Jiun Chuang, Michael Appell
ACS Omega (2023) Vol. 8, Iss. 18, pp. 15854-15864
Open Access | Times Cited: 19
Will we ever be able to accurately predict solubility?
Pierre Llompart, Claire Minoletti, Shamkhal Baybekov, et al.
Scientific Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 6
Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
Tomasz Jeliński, Maciej Przybyłek, Rafał Różalski, et al.
Polymers in Medicine (2024) Vol. 54, Iss. 1, pp. 15-25
Open Access | Times Cited: 5
Screening of the Antagonistic Activity of Potential Bisphenol A Alternatives toward the Androgen Receptor Using Machine Learning and Molecular Dynamics Simulation
Zeguo Yang, Ling Wang, Ying Yang, et al.
Environmental Science & Technology (2024) Vol. 58, Iss. 6, pp. 2817-2829
Closed Access | Times Cited: 5
Artificial Intelligence Assisted Pharmaceutical Crystallization
Zuoxuan Zhu, Yuan Zhang, Zhixuan Wang, et al.
Crystal Growth & Design (2024) Vol. 24, Iss. 10, pp. 4245-4270
Closed Access | Times Cited: 5
Artificial intelligence in antidiabetic drug discovery: The advances in QSAR and the prediction of α-glucosidase inhibitors
Adeshina I. Odugbemi, Clement N. Nyirenda, Alan Christoffels, et al.
Computational and Structural Biotechnology Journal (2024) Vol. 23, pp. 2964-2977
Open Access | Times Cited: 5
Machine Learning-Based Prediction of Drug Solubility in Lipidic Environments: The Sol_ME Tool for Optimizing Lipid-Based Formulations with a Preliminary Apalutamide Case Study
Swayamprakash Patel, Ami Kalasariya, Jagruti Desai, et al.
AAPS PharmSciTech (2025) Vol. 26, Iss. 2
Closed Access
Improved Prediction Model of Protein and Peptide Toxicity by Integrating Channel Attention into a Convolutional Neural Network and Gated Recurrent Units
Zhengyun Zhao, Jingyu Gui, Anqi Yao, et al.
ACS Omega (2022) Vol. 7, Iss. 44, pp. 40569-40577
Open Access | Times Cited: 24
Blinded Predictions and Post Hoc Analysis of the Second Solubility Challenge Data: Exploring Training Data and Feature Set Selection for Machine and Deep Learning Models
Jonathan G. M. Conn, James W. Carter, Justin J. A. Conn, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 4, pp. 1099-1113
Open Access | Times Cited: 13
Experimental analysis and prediction of radionuclide solubility using machine learning models: Effects of organic complexing agents
Bolam Kim, Amaranadha Reddy Manchuri, Gi-Taek Oh, et al.
Journal of Hazardous Materials (2024) Vol. 469, pp. 134012-134012
Closed Access | Times Cited: 4
Enhancing Copolymer Property Prediction through the Weighted-Chained-SMILES Machine Learning Framework
Qi Huang, Zuowei Chen, Ziwei Lin, et al.
ACS Applied Polymer Materials (2024) Vol. 6, Iss. 7, pp. 3666-3675
Open Access | Times Cited: 4
Experimental and Theoretical Insights into the Intermolecular Interactions in Saturated Systems of Dapsone in Conventional and Deep Eutectic Solvents
Piotr Cysewski, Tomasz Jeliński, Maciej Przybyłek
Molecules (2024) Vol. 29, Iss. 8, pp. 1743-1743
Open Access | Times Cited: 4
Machine learning-assisted rheumatoid arthritis formulations: A review on smart pharmaceutical design
Niki Pouyanfar, Zahra Anvari, Kamyar Davari-Kia, et al.
Materials Today Communications (2024) Vol. 41, pp. 110208-110208
Closed Access | Times Cited: 4
Free Energy Perturbation Approach for Accurate Crystalline Aqueous Solubility Predictions
Richard S. Hong, Ana V. Rojas, Rajni M. Bhardwaj, et al.
Journal of Medicinal Chemistry (2023) Vol. 66, Iss. 23, pp. 15883-15893
Closed Access | Times Cited: 10
Scientific Deep Machine Learning Concepts for the Prediction of Concentration Profiles and Chemical Reaction Kinetics: Consideration of Reaction Conditions
Niklas Adebar, Julian Keupp, Victor N. Emenike, et al.
The Journal of Physical Chemistry A (2024) Vol. 128, Iss. 5, pp. 929-944
Closed Access | Times Cited: 3
Eco‐Friendly Materials for a Zero E‐Waste Society: Challenges and Opportunities in Engineering Plastics
Seunghyeon Lee, Minhu Huang, Junhyuk Lee, et al.
Advanced Sustainable Systems (2024) Vol. 8, Iss. 7
Closed Access | Times Cited: 3
A Machine Learning Approach for the Prediction of Aqueous Solubility of Pharmaceuticals: A Comparative Model and Dataset Analysis
Mohammad Amin Ghanavati, Soroush Ahmadi, Sohrab Rohani
Digital Discovery (2024)
Open Access | Times Cited: 3
Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
Piotr Cysewski, Tomasz Jeliński, Maciej Przybyłek, et al.
Pharmaceutics (2022) Vol. 14, Iss. 12, pp. 2828-2828
Open Access | Times Cited: 15
Advancing algorithmic drug product development: Recommendations for machine learning approaches in drug formulation
Jack D. Murray, Justus Johann Lange, Harriet Bennett-Lenane, et al.
European Journal of Pharmaceutical Sciences (2023) Vol. 191, pp. 106562-106562
Open Access | Times Cited: 8
Enhancing Hansen Solubility Predictions with Molecular and Graph-Based Approaches
Darja Cvetković, Marija Mitrović, Aleksandar Bogojević, et al.
Chemometrics and Intelligent Laboratory Systems (2024) Vol. 251, pp. 105168-105168
Closed Access | Times Cited: 2
Graph Neural Networks for Predicting Solubility in Diverse Solvents Using MolMerger Incorporating Solute–Solvent Interactions
Vansh Ramani, Tarak Karmakar
Journal of Chemical Theory and Computation (2024) Vol. 20, Iss. 15, pp. 6549-6558
Open Access | Times Cited: 2
Extended study on atomic featurization in graph neural networks for molecular property prediction
Agnieszka Wojtuch, Tomasz Danel, Sabina Podlewska, et al.
Journal of Cheminformatics (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 7
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