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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:

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

Showing 26-50 of 61 citing articles:

PERISCOPE-Opt: Machine learning-based prediction of optimal fermentation conditions and yields of recombinant periplasmic protein expressed in Escherichia coli
Kulandai Arockia Rajesh Packiam, Chien Wei Ooi, Fuyi Li, et al.
Computational and Structural Biotechnology Journal (2022) Vol. 20, pp. 2909-2920
Open Access | Times Cited: 14
SIDERITE: Unveiling Hidden Siderophore Diversity in the Chemical Space Through Digital Exploration
Ruolin He, Shaohua Gu, Jiazheng Xu, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 7
Solubility Behavior of α-Aminoisobutyric Acid in 13 Individual Solvents at Temperatures Ranging from 283.15 to 323.15 K
Mingyu Jing, Yongjie Wang, Dandan Liu, et al.
Journal of Chemical & Engineering Data (2024) Vol. 69, Iss. 5, pp. 2003-2015
Closed Access | Times Cited: 2
Expanding Chemical Representation with k-mers and Fragment-Based Fingerprints for Molecular Fingerprinting
Sarwan Ali, Prakash Chourasia, Murray Patterson
Communications in computer and information science (2024), pp. 17-29
Closed Access | Times Cited: 2
Graph Neural Networks for Predicting Solubility in Diverse Solvents Using MolMerger Incorporating Solute–Solvent Interactions
Vansh Ramani, Tarak Karmakar
Journal of Chemical Theory and Computation (2024) Vol. 20, Iss. 15, pp. 6549-6558
Open Access | Times Cited: 2
Predicting Solubility Limits of Organic Solutes for a Wide Range of Solvents and Temperatures
Florence H. Vermeire, Yunsie Chung, William H. Green
(2022)
Open Access | Times Cited: 13
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
Predicting the Solubility of Organic Energy Storage Materials Based on Functional Group Identity and Substitution Pattern
Madison R. Tuttle, Emma Brackman, Farshud Sorourifar, et al.
The Journal of Physical Chemistry Letters (2023) Vol. 14, Iss. 5, pp. 1318-1325
Closed Access | Times Cited: 6
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
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
Insights into the Vibrio Genus: A One Health Perspective from Host Adaptability and Antibiotic Resistance to In Silico Identification of Drug Targets
Pedro Henrique Marques, Lígia Carolina da Silva Prado, Andrei Giacchetto Felice, et al.
Antibiotics (2022) Vol. 11, Iss. 10, pp. 1399-1399
Open Access | Times Cited: 7
Multi-channel GCN ensembled machine learning model for molecular aqueous solubility prediction on a clean dataset
Chenglong Deng, Li Liang, Guomeng Xing, et al.
Molecular Diversity (2022) Vol. 27, Iss. 3, pp. 1023-1035
Closed Access | Times Cited: 6
Explaining structure-activity relationships using locally faithful surrogate models
Heta A. Gandhi, Andrew Dickson White
(2022)
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
Integrating digital chemistry within the broader chemistry community
David Dalmau, Juan V. Alegre‐Requena
Trends in Chemistry (2024) Vol. 6, Iss. 8, pp. 459-469
Closed Access
What can attribution methods show us about chemical language models?
Stefan Hödl, Tal Kachman, Yoram Bachrach, et al.
Digital Discovery (2024) Vol. 3, Iss. 9, pp. 1738-1748
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
WaSPred: A reliable AI-based water solubility predictor for small molecules
Miriana Di Stefano, Salvatore Galati, Chiara Lonzi, et al.
International Journal of Pharmaceutics (2024) Vol. 666, pp. 124817-124817
Closed 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
Development of Drug-Induced Gene Expression Ranking Analysis (DIGERA) and Its Application to Virtual Screening for Poly (ADP-Ribose) Polymerase 1 Inhibitor
Hyein Cho, Kyoung Tai No, Hocheol Lim
International Journal of Molecular Sciences (2024) Vol. 26, Iss. 1, pp. 224-224
Open Access
An interpretable graph representation learning model for accurate predictions of drugs aqueous solubility
Qiufen Chen, Yuewei Zhang, Peng Gao, et al.
Artificial Intelligence Chemistry (2023) Vol. 1, Iss. 2, pp. 100010-100010
Open Access | Times Cited: 1
Machine-Learning-Enabled Ligand Screening for Cs/Sr Crystallizing Separation
Bingbing Wang, Zhiyuan Zhang, Yue Dong, et al.
Inorganic Chemistry (2023) Vol. 62, Iss. 33, pp. 13293-13303
Closed 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

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