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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:

Findings of the Second Challenge to Predict Aqueous Solubility
Antonio Llinàs, Ioana Oprisiu, Alex Avdeef
Journal of Chemical Information and Modeling (2020) Vol. 60, Iss. 10, pp. 4791-4803
Closed Access | Times Cited: 54

Showing 26-50 of 54 citing articles:

Intrinsic Aqueous Solubility: Mechanistically Transparent Data-Driven Modeling of Drug Substances
Mare Oja, Sulev Sild, Geven Piir, et al.
Pharmaceutics (2022) Vol. 14, Iss. 10, pp. 2248-2248
Open Access | Times Cited: 12
Reversible interconversion of pharmaceutical salt polymorphs facilitated by mechanical methods
Liulei Ma, Qixuan Zheng, Daniel K. Unruh, et al.
Chemical Communications (2023) Vol. 59, Iss. 50, pp. 7779-7782
Open Access | Times Cited: 6
Leveraging genetic algorithms to maximise the predictive capabilities of the SOAP descriptor
Trent Barnard, Steven Tseng, James P. Darby, et al.
Molecular Systems Design & Engineering (2022) Vol. 8, Iss. 3, pp. 300-315
Open Access | Times Cited: 10
Designing solvent systems using self-evolving solubility databases and graph neural networks
Yeonjoon Kim, Hojin Jung, Sabari Kumar, et al.
Chemical Science (2023) Vol. 15, Iss. 3, pp. 923-939
Open Access | Times Cited: 5
Predicting small molecules solubility on endpoint devices using deep ensemble neural networks
Mayk Caldas Ramos, Andrew Dickson White
Digital Discovery (2024) Vol. 3, Iss. 4, pp. 786-795
Open Access | Times Cited: 1
MacroConf – dataset & workflows to assess cyclic peptide solution structures
Daniel Crusius, Jason R. Schnell, Flaviu Cipcigan, et al.
Digital Discovery (2023) Vol. 2, Iss. 4, pp. 1163-1177
Open 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
Salt Solubility and Disproportionation – Uses and Limitations of Equations for pHmax and the In-silico Prediction of pHmax
Alex Avdeef, Kiyohiko Sugano
Journal of Pharmaceutical Sciences (2021) Vol. 111, Iss. 1, pp. 225-246
Open Access | Times Cited: 9
Explaining structure-activity relationships using locally faithful surrogate models
Heta A. Gandhi, Andrew Dickson White
(2022)
Open Access | Times Cited: 5
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
Recent Studies of Artificial Intelligence on In Silico Drug Absorption
Thi Tuyet Van Tran, Hilal Tayara, Kil To Chong
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 20, pp. 6198-6211
Closed 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
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
In Silico ADME Modeling
Gerhard F. Ecker
Springer eBooks (2024), pp. 1-27
Closed 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
Advancements in Solubility Enhancement of Omeprazole: A Comprehensive Review
Taufik Mulla, Mrunali Nemade, Tahoora Ansari, et al.
Research Journal of Pharmaceutical Dosage Forms and Technology (2024), pp. 163-172
Closed 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
GGAS2SN: Gated Graph and SmilesToSeq Network for Solubility Prediction
Waqar Ahmad, Kil To Chong, Hilal Tayara
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 20, pp. 7833-7843
Closed Access
In Silico ADME Modeling
Gerhard F. Ecker
Springer eBooks (2024), pp. 1901-1927
Closed Access
Machine Learning for Solubility Prediction
Tianyuan Zheng, John B. O. Mitchell, Simon Dobson
Research Square (Research Square) (2023)
Open Access | Times Cited: 1
Ensemble Geometric Deep Learning of Aqueous Solubility
Mohammad Mehdi Ghahremanpour, Anastasia Saar, Julian Tirado‐Rives, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 23, pp. 7338-7349
Closed 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
Explaining structure-activity relationships using locally faithful surrogate models
Heta A. Gandhi, Andrew Dickson White
(2022)
Open Access | Times Cited: 1
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

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