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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 in prediction of intrinsic aqueous solubility of drug‐like compounds: Generalization, complexity, or predictive ability?
Mario Lovrić, Kristina Pavlović, Petar Žuvela, et al.
Journal of Chemometrics (2021) Vol. 35, Iss. 7-8
Open Access | Times Cited: 51

Showing 1-25 of 51 citing articles:

SolTranNet–A Machine Learning Tool for Fast Aqueous Solubility Prediction
Paul Francoeur, David Ryan Koes
Journal of Chemical Information and Modeling (2021) Vol. 61, Iss. 6, pp. 2530-2536
Open Access | Times Cited: 61
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
A unified ML framework for solubility prediction across organic solvents
Antony D. Vassileiou, Murray N. Robertson, Bruce G. Wareham, et al.
Digital Discovery (2023) Vol. 2, Iss. 2, pp. 356-367
Open Access | Times Cited: 22
Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
Piotr Cysewski, Tomasz Jeliński, Maciej Przybyłek, et al.
Molecules (2024) Vol. 29, Iss. 10, pp. 2296-2296
Open Access | Times Cited: 11
SolPredictor: Predicting Solubility with Residual Gated Graph Neural Network
Waqar Ahmad, Hilal Tayara, Hyun Joo Shim, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 2, pp. 715-715
Open Access | Times Cited: 10
Deep Eutectic Solvents Enhancing Drug Solubility and Its Delivery
Anshu Sharma, Y PARK, Aman Garg, et al.
Journal of Medicinal Chemistry (2024) Vol. 67, Iss. 17, pp. 14807-14819
Closed Access | Times Cited: 7
Refined ADME Profiles for ATC Drug Classes
Luca Menestrina, Raquel Parrondo-Pizarro, Ismael Gómez, et al.
Pharmaceutics (2025) Vol. 17, Iss. 3, pp. 308-308
Open Access
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
Optimization of Bacterial Cellulose Production by Komagataeibacter rhaeticus K23
Ceyda Uğurel, Hamdi Öğüt
Fibers (2024) Vol. 12, Iss. 3, pp. 29-29
Open Access | Times Cited: 6
Development of Prediction Models for Shear Strength of Rockfill Material Using Machine Learning Techniques
Mahmood Ahmad, Paweł Kamiński, Piotr Olczak, et al.
Applied Sciences (2021) Vol. 11, Iss. 13, pp. 6167-6167
Open Access | Times Cited: 38
In Silico Prediction of the Toxicity of Nitroaromatic Compounds: Application of Ensemble Learning QSAR Approach
Amirreza Daghighi, Gerardo M. Casañola‐Martín, Troy Timmerman, et al.
Toxics (2022) Vol. 10, Iss. 12, pp. 746-746
Open Access | Times Cited: 23
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
Bridging the Gap between Differential Mobility, Log S, and Log P Using Machine Learning and SHAP Analysis
Cailum Stienstra, Christian Ieritano, Alexander Haack, et al.
Analytical Chemistry (2023) Vol. 95, Iss. 27, pp. 10309-10321
Closed Access | Times Cited: 12
Exploration of the Solubility Hyperspace of Selected Active Pharmaceutical Ingredients in Choline- and Betaine-Based Deep Eutectic Solvents: Machine Learning Modeling and Experimental Validation
Piotr Cysewski, Tomasz Jeliński, Maciej Przybyłek
Molecules (2024) Vol. 29, Iss. 20, pp. 4894-4894
Open Access | Times Cited: 4
Vertical Metabolome Transfer from Mother to Child: An Explainable Machine Learning Method for Detecting Metabolomic Heritability
Mario Lovrić, David A. Horner, Liang Chen, et al.
Metabolites (2024) Vol. 14, Iss. 3, pp. 136-136
Open Access | Times Cited: 3
Tuning Ferulic Acid Solubility in Choline-Chloride- and Betaine-Based Deep Eutectic Solvents: Experimental Determination and Machine Learning Modeling
Tomasz Jeliński, Maciej Przybyłek, Rafał Różalski, et al.
Molecules (2024) Vol. 29, Iss. 16, pp. 3841-3841
Open 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
Be aware of overfitting by hyperparameter optimization!
Igor V. Tetko, Ruud van Deursen, Guillaume Godin
Journal of Cheminformatics (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 3
Should We Embed in Chemistry? A Comparison of Unsupervised Transfer Learning with PCA, UMAP, and VAE on Molecular Fingerprints
Mario Lovrić, Tomislav Đuričić, Han Tran, et al.
Pharmaceuticals (2021) Vol. 14, Iss. 8, pp. 758-758
Open Access | Times Cited: 23
Machine Learning and Meteorological Normalization for Assessment of Particulate Matter Changes during the COVID-19 Lockdown in Zagreb, Croatia
Mario Lovrić, Mario Antunović, Iva Šunić, et al.
International Journal of Environmental Research and Public Health (2022) Vol. 19, Iss. 11, pp. 6937-6937
Open Access | Times Cited: 16
Transparency in Modeling through Careful Application of OECD’s QSAR/QSPR Principles via a Curated Water Solubility Data Set
Charles Lowe, Nathaniel Charest, Christian Ramsland, et al.
Chemical Research in Toxicology (2023) Vol. 36, Iss. 3, pp. 465-478
Closed Access | Times Cited: 9
Machine learning-based soil quality assessment for enhancing environmental monitoring in iron ore mining-impacted ecosystems
Helena Santiago Lima, Gustavo Ferreira Viegas de Oliveira, Ricardo dos Santos Ferreira, et al.
Journal of Environmental Management (2024) Vol. 356, pp. 120559-120559
Closed Access | Times Cited: 2
Prediction Technology of a Reservoir Development Model While Drilling Based on Machine Learning and Its Application
Xin Wang, Min Mao, Yi Yang, et al.
Processes (2024) Vol. 12, Iss. 5, pp. 975-975
Open Access | Times Cited: 2
Comparative Analysis of Chemical Descriptors by Machine Learning Reveals Atomistic Insights into Solute–Lipid Interactions
Justus Johann Lange, Andrea Anelli, Jochem Alsenz, et al.
Molecular Pharmaceutics (2024) Vol. 21, Iss. 7, pp. 3343-3355
Open Access | Times Cited: 2
Predicting Treatment Outcomes Using Explainable Machine Learning in Children with Asthma
Mario Lovrić, Ivana Banić, Emanuel Lacić, et al.
Children (2021) Vol. 8, Iss. 5, pp. 376-376
Open Access | Times Cited: 19
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