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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.

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Showing 1-25 of 51 citing articles:

Fungicide compound 2, 3-dichloronaphthalene-1, 4-dione: Non-covalent interactions (QTAIM, RDG and ELF), combined vibrational spectroscopic investigations using DFT approach with experimental analysis, electronic, molecular docking scrutiny in-vitro assay and thermodynamic property analysis
P. Divya, V.S. Jeba Reeda, V. Bena Jothy
Journal of Molecular Liquids (2024) Vol. 400, pp. 124544-124544
Closed Access | Times Cited: 21
Spectroscopic characterization (IR, UV-Vis), and HOMO-LUMO, MEP, NLO, NBO Analysis and the Antifungal Activity for 4-Bromo-N-(2-nitrophenyl) benzamide; Using DFT Modeling and In silico Molecular Docking
Suzan K. Alghamdi, Faheem Abbas, Rageh K. Hussein, et al.
Journal of Molecular Structure (2022) Vol. 1271, pp. 134001-134001
Closed Access | Times Cited: 57
DFT, ADMET and Molecular Docking Investigations for the Antimicrobial Activity of 6,6′-Diamino-1,1′,3,3′-tetramethyl-5,5′-(4-chlorobenzylidene)bis[pyrimidine-2,4(1H,3H)-dione]
N.T. El‐Shamy, A. Alkaoud, Rageh K. Hussein, et al.
Molecules (2022) Vol. 27, Iss. 3, pp. 620-620
Open Access | Times Cited: 50
Discovery solubility measurement and assessment of small molecules with drug development in mind
Jaclyn A. Barrett, Wenzhan Yang, Suzanne Skolnik, et al.
Drug Discovery Today (2022) Vol. 27, Iss. 5, pp. 1315-1325
Closed Access | Times Cited: 44
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
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
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
AI-ML applications in bioprocessing: ML as an enabler of real time quality prediction in continuous manufacturing of mAbs
Saxena Nikita, Garima Thakur, Naveen G. Jesubalan, et al.
Computers & Chemical Engineering (2022) Vol. 164, pp. 107896-107896
Closed Access | Times Cited: 33
Machine learning methods for pKa prediction of small molecules: Advances and challenges
Jialu Wu, Yu Kang, Peichen Pan, et al.
Drug Discovery Today (2022) Vol. 27, Iss. 12, pp. 103372-103372
Closed Access | Times Cited: 28
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
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
Online OCHEM multi-task model for solubility and lipophilicity prediction of platinum complexes
Nesma Mousa, Hristo P. Varbanov, K. Vidya, et al.
Journal of Inorganic Biochemistry (2025), pp. 112890-112890
Open Access
Pushing the limits of solubility prediction via quality-oriented data selection
Murat Cihan Sorkun, J. M. V. A. Koelman, Süleyman Er
iScience (2020) Vol. 24, Iss. 1, pp. 101961-101961
Open Access | Times Cited: 43
Predicting Solubility of Newly-Approved Drugs (2016–2020) with a Simple ABSOLV and GSE(Flexible-Acceptor) Consensus Model Outperforming Random Forest Regression
Alex Avdeef, Manfred Kansy
Journal of Solution Chemistry (2022) Vol. 51, Iss. 9, pp. 1020-1055
Open Access | Times Cited: 22
General Graph Neural Network-Based Model To Accurately Predict Cocrystal Density and Insight from Data Quality and Feature Representation
Jiali Guo, Ming Sun, Xueyan Zhao, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 4, pp. 1143-1156
Closed Access | Times Cited: 13
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
Application of Artificial Neural Networks to Predict the Intrinsic Solubility of Drug-Like Molecules
Elena M. Tosca, Roberta Bartolucci, Paolo Magni
Pharmaceutics (2021) Vol. 13, Iss. 7, pp. 1101-1101
Open Access | Times Cited: 24
ADME Prediction with KNIME: In silico aqueous solubility models based on supervised recursive machine learning approaches
Gabriela Falcón-Cano, Christophe Molina, Miguel Ángel Cabrera‐Pérez
ADMET & DMPK (2020)
Open Access | Times Cited: 24
Artificial Intelligence, Machine Learning, and Deep Learning in Real-Life Drug Design Cases
Christophe Müller, Obdulia Rabal, Constantino Diaz Gonzalez
Methods in molecular biology (2021), pp. 383-407
Closed Access | Times Cited: 21
“Flexible-Acceptor” General Solubility Equation for beyond Rule of 5 Drugs
Alex Avdeef, Manfred Kansy
Molecular Pharmaceutics (2020) Vol. 17, Iss. 10, pp. 3930-3940
Closed Access | Times Cited: 23
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
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
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.
(2020)
Open Access | Times Cited: 14
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