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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:

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

Showing 13 citing articles:

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
The Application of Information Technology for Athlete Data Analysis and Automatic Generation of Training Plans
Yuan Shu-li
Scalable Computing Practice and Experience (2024) Vol. 25, Iss. 5, pp. 4376-4382
Open Access | Times Cited: 3
Comprehensive applications of the artificial intelligence technology in new drug research and development
Hongyu Chen, Dong Xin Lu, Ziyi Xiao, et al.
Health Information Science and Systems (2024) Vol. 12, Iss. 1
Closed Access | Times Cited: 3
Evaluating Machine Learning Methods of Analyzing Multiclass Metabolomics
Yaguo Gong, Wei Ding, Panpan Wang, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 24, pp. 7628-7641
Closed Access | Times Cited: 9
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
Utilizing machine learning-based QSAR model to overcome standalone consensus docking limitation in beta-lactamase inhibitors screening: a proof-of-concept study
Thanet Pitakbut, Jennifer Munkert, Wenhui Xi, et al.
BMC Chemistry (2024) Vol. 18, Iss. 1
Open Access | Times Cited: 1
Predicting sulfanilamide solubility in mixed solvents: A comparative analysis of computational models
Prashanth Asadi, Kalyani Kodide, Jyothi Thati, et al.
Fluid Phase Equilibria (2023) Vol. 577, pp. 113966-113966
Closed Access | Times Cited: 3
Chemical space analysis and property prediction for carbon capture solvent molecules
James L. McDonagh, Stamatia Zavitsanou, Alexander Harrison, et al.
Digital Discovery (2024) Vol. 3, Iss. 3, pp. 528-543
Open Access
In Silico ADME Modeling
Gerhard F. Ecker
Springer eBooks (2024), pp. 1-27
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
In Silico ADME Modeling
Gerhard F. Ecker
Springer eBooks (2024), pp. 1901-1927
Closed Access
A Machine Learning Free Energy Functional for the 1D Reference Interaction Site Model: Towards Prediction of Solvation Free Energy for All Solvent Systems
Jonathan G. M. Conn, Abdullah Ahmad, David Scott Palmer
Liquids (2024) Vol. 4, Iss. 4, pp. 710-731
Open Access
CHEMICAL SPACE ANALYSIS AND PROPERTY PREDICTION FOR CARBON CAPTURE AMINE MOLECULES
James L. McDonagh, Stamatia Zavitsanou, Alexander Harrison, et al.
(2023)
Open Access
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