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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:

Solubility Challenge Revisited after Ten Years, with Multilab Shake-Flask Data, Using Tight (SD ∼ 0.17 log) and Loose (SD ∼ 0.62 log) Test Sets
Antonio Llinàs, Alex Avdeef
Journal of Chemical Information and Modeling (2019) Vol. 59, Iss. 6, pp. 3036-3040
Closed Access | Times Cited: 50

Showing 26-50 of 50 citing articles:

Comparative assessment of physics-based in silico methods to calculate relative solubilities
Adiran Garaizar Suarez, Andreas H. Göller, Michael E. Beck, et al.
Journal of Computer-Aided Molecular Design (2024) Vol. 38, Iss. 1
Closed Access | Times Cited: 1
ALipSol: An Attention-Driven Mixture-of-Experts Model for Lipophilicity and Solubility Prediction
Jialu Wu, Junmei Wang, Zhenhua Wu, et al.
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 23, pp. 5975-5987
Closed Access | Times Cited: 8
Abraham general solvation parameter model: intramolecular hydrogen bond formation and its effect on the A- and B-descriptor values of select tetracycline derivatives
Emily J. Yao, William E. Acree
Physics and Chemistry of Liquids (2023) Vol. 62, Iss. 1, pp. 25-33
Closed Access | Times Cited: 4
Trends in PhysChem Properties of Newly Approved Drugs over the Last Six Years; Predicting Solubility of Drugs Approved in 2021
Alex Avdeef, Manfred Kansy
Journal of Solution Chemistry (2022) Vol. 51, Iss. 12, pp. 1455-1481
Closed Access | Times Cited: 7
Potentiometric Titration Method for the Determination of Solubility Limits and pKa Values of Weak Organic Acids in Water
Eduard Wiedenbeck, Denis Gebauer, Helmut Cölfen
Analytical Chemistry (2020) Vol. 92, Iss. 14, pp. 9511-9515
Closed Access | Times Cited: 10
Three machine learning models for the 2019 Solubility Challenge
John B. O. Mitchell
ADMET & DMPK (2020)
Open Access | Times Cited: 10
Do you know your r2?
Alex Avdeef
ADMET & DMPK (2020)
Open Access | Times Cited: 10
Dealing with a data-limited regime: Combining transfer learning and transformer attention mechanism to increase aqueous solubility prediction performance
Magdalena Wiercioch, Johannes Kirchmair
Artificial Intelligence in the Life Sciences (2021) Vol. 1, pp. 100021-100021
Open Access | Times Cited: 9
In Silico ADME Modeling
Ioana Oprisiu, Susanne Winiwarter
Elsevier eBooks (2019), pp. 208-222
Closed Access | Times Cited: 7
Mechanistically transparent models for predicting aqueous solu¬bility of rigid, slightly flexible, and very flexible drugs (MW<2000) Accuracy near that of random forest regression Alex Avdeef
Alex Avdeef
ADMET & DMPK (2023)
Open Access | Times Cited: 2
Predicting absolute aqueous solubility by applying a machine learning model for an artificially liquid-state as proxy for the solid-state
Sadra Kashef Ol Gheta, Anne Bonin, Thomas Gerlach, et al.
Journal of Computer-Aided Molecular Design (2023) Vol. 37, Iss. 12, pp. 765-789
Closed Access | Times Cited: 2
Simple Method (CHEM-SP) to Predict Solubility from 2-D Chemical Structures
Jun Qiu, Jun Li, Jacob Albrecht, et al.
Organic Process Research & Development (2020) Vol. 25, Iss. 1, pp. 75-81
Closed Access | Times Cited: 5
ADME prediction with KNIME: A retrospective contribution to the second “Solubility Challenge”
Gabriela Falcón-Cano, Christophe Molina, Miguel Ángel Cabrera‐Pérez
ADMET & DMPK (2021)
Open Access | Times Cited: 5
Correction: Predicting small molecules solubility on endpoint devices using deep ensemble neural networks
Mayk Caldas Ramos, Andrew Dickson White
Digital Discovery (2024) Vol. 3, Iss. 5, pp. 1069-1070
Open Access
Solvmate – a hybrid physical/ML approach to solvent recommendation leveraging a rank-based problem framework
Jan M. Wollschläger, Floriane Montanari
Digital Discovery (2024) Vol. 3, Iss. 9, pp. 1749-1760
Open Access
Revisiting the Application of Machine Learning Approaches in Predicting Aqueous Solubility
Tianyuan Zheng, John B. O. Mitchell, Simon Dobson
ACS Omega (2024) Vol. 9, Iss. 32, pp. 35209-35222
Open Access
Effect of Data Quality and Data Quantity on the Estimation of Intrinsic Solubility: Analysis Based on a Single-Source Data Set
J Q Zhao, Eline Hermans, Kia Sepassi, et al.
Molecular Pharmaceutics (2024)
Open Access
Thermodynamic Correlation between Liquid–Liquid Phase Separation and Crystalline Solubility of Drug-Like Molecules
Taiga Uekusa, Tomohiro Watanabe, Daiju Watanabe, et al.
Pharmaceutics (2022) Vol. 14, Iss. 12, pp. 2560-2560
Open Access | Times Cited: 3
Machine Learning for Solubility Prediction
Tianyuan Zheng, John B. O. Mitchell, Simon Dobson
Research Square (Research Square) (2023)
Open Access | Times Cited: 1
Solubility and Solvent Effect Analysis of Boc-l-glutamine in Different Solvents at Multiple Temperatures
Dandan Liu, Jingxuan Qiu, Shen Hu, et al.
Journal of Chemical & Engineering Data (2022) Vol. 67, Iss. 6, pp. 1573-1581
Closed Access | Times Cited: 2
Machine Learning for FB Electrolyte Screening
Laura‐Sophie Berg, Jan Hamaekers, Astrid Maaß
(2023), pp. 487-506
Closed Access
Designing solvent systems in chemical processes using self-evolving solubility databases and graph neural networks
Yeonjoon Kim, Hojin Jung, Sabari Kumar, et al.
(2023)
Open Access
Liquid-Liquid Phase Separation at the Surface of Dissolving Drug Salt Particles: Prediction
Anfal Albalool
International Journal of Medical Arts (2023) Vol. 5, Iss. 11, pp. 3838-3847
Open Access
Trends in PhysChem Properties of Newly Approved Drugs over the Last Six Years; Predicting Solubility of Drugs Approved in 2021
Alex Avdeef, Manfred Kansy
Research Square (Research Square) (2022)
Open Access
Designing solvent systems in chemical processes using self-evolving solubility databases and graph neural networks
Yeonjoon Kim, Hojin Jung, Sabari Kumar, et al.
(2022)
Open Access
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