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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:

Validation of Acetylcholinesterase Inhibition Machine Learning Models for Multiple Species
Patricia A. Vignaux, Thomas R. Lane, Fabio Urbina, et al.
Chemical Research in Toxicology (2023) Vol. 36, Iss. 2, pp. 188-201
Open Access | Times Cited: 11

Showing 11 citing articles:

Dual inhibition of AChE and MAO-B in Alzheimer’s disease: machine learning approaches and model interpretations
Qinghe Hou, Yan Li
Molecular Diversity (2025)
Open Access
Progress, applications, and challenges in high-throughput effect-directed analysis for toxicity driver identification — is it time for HT-EDA?
Iker Alvarez-Mora, Katarzyna Arturi, Frederic Béen, et al.
Analytical and Bioanalytical Chemistry (2024)
Open Access | Times Cited: 4
Artificial intelligence in clinical pharmacology: A case study and scoping review of large language models and bioweapon potential
Igor Rubinić, Marija Kurtov, Ivan Rubinić, et al.
British Journal of Clinical Pharmacology (2023) Vol. 90, Iss. 3, pp. 620-628
Closed Access | Times Cited: 10
Sequential Contrastive and Deep Learning Models to Identify Selective Butyrylcholinesterase Inhibitors
Mustafa Kemal Ozalp, Patricia A. Vignaux, Ana C. Puhl, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 8, pp. 3161-3172
Closed Access | Times Cited: 2
The Goldilocks paradigm: comparing classical machine learning, large language models, and few-shot learning for drug discovery applications
Scott Snyder, Patricia A. Vignaux, Mustafa Kemal Ozalp, et al.
Communications Chemistry (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 2
Introduction to the Special Issue: AI Meets Toxicology
Günter Klambauer, Djork-Arné Clevert, Imran Shah, et al.
Chemical Research in Toxicology (2023) Vol. 36, Iss. 8, pp. 1163-1167
Closed Access | Times Cited: 6
Eucalyptus globulus leaf-isolated isorhapontin serves as a natural insecticide via acetylcholinesterase inhibition
Jae Yeon Park, Seong Doo Kang, Yun Gon Son, et al.
Pesticide Biochemistry and Physiology (2024) Vol. 200, pp. 105834-105834
Closed Access | Times Cited: 1
Improved QSAR models for PARP-1 inhibition using data balancing, interpretable machine learning, and matched molecular pair analysis
Anish Gomatam, Bhakti Umesh Hirlekar, Krishan Dev Singh, et al.
Molecular Diversity (2024) Vol. 28, Iss. 4, pp. 2135-2152
Closed Access | Times Cited: 1
Secondary metabolites in Cordyceps javanica with insecticidal potential
Pei‐Xiang Xing, Ruixia Mao, Guisen Zhang, et al.
Pesticide Biochemistry and Physiology (2024) Vol. 204, pp. 106076-106076
Closed Access
Repurposing Lapatinib as a Triple Antagonist of Chemokine Receptors 3, 4 and 5
Thomas R. Lane, Ana C. Puhl, Patricia A. Vignaux, et al.
Molecular Pharmacology (2024) Vol. 107, Iss. 1, pp. 100010-100010
Closed Access
Dual Inhibition of AChE and MAO-B in Alzheimer's Disease: Machine Learning Approaches and Model Interpretations
Qinghe Hou, Yan Li
Research Square (Research Square) (2024)
Closed Access
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