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:

QSAR-QSIIR-based prediction of bioconcentration factor using machine learning and preliminary application
Jiayun Xu, Kun Wang, Shuhui Men, et al.
Environment International (2023) Vol. 177, pp. 108003-108003
Open Access | Times Cited: 15

Showing 15 citing articles:

Applications of conceptual density functional theory in reference to quantitative structure–activity / property relationship
Pooja Sharma, Prabhat Ranjan, Tanmoy Chakraborty
Molecular Physics (2024) Vol. 122, Iss. 23
Open Access | Times Cited: 7

Exploring pollutant joint effects in disease through interpretable machine learning
Shuo Wang, Tianzhuo Zhang, Ziheng Li, et al.
Journal of Hazardous Materials (2024) Vol. 467, pp. 133707-133707
Closed Access | Times Cited: 4

Regulation roles of dre-miR-187 in neurological damage by low concentration toluene in zebrafish
Shuhui Men, Jiayun Xu, Zhenguang Yan, et al.
Journal of Cleaner Production (2025), pp. 144973-144973
Closed Access

Computational Toxicology and Risk Assessment
Brad Reisfeld, Sherif Farag
Elsevier eBooks (2025)
Closed Access

Machine Learning-based q-RASAR Predictions of the Bioconcentration Factor of Organic Molecules Estimated Following the Organisation for Economic Co-operation and Development Guideline 305
Souvik Pore, A. Pelloux, Mainak Chatterjee, et al.
Journal of Hazardous Materials (2024) Vol. 479, pp. 135725-135725
Closed Access | Times Cited: 3

Ecological Risk Assessment of Organochlorine Pesticides and Polychlorinated Biphenyls in Coastal Sediments in China
Jie Wang, Qi Zhao, Fu Gao, et al.
Toxics (2024) Vol. 12, Iss. 2, pp. 114-114
Open Access | Times Cited: 2

Molecular designing of potential environmentally friendly PFAS based on deep learning and generative models
Ying Yang, Zeguo Yang, Xudi Pang, et al.
The Science of The Total Environment (2024) Vol. 953, pp. 176095-176095
Closed Access | Times Cited: 1

Advancing food safety risk assessment in China: development of new approach methodologies (NAMs)
Daoyuan Yang, Hui Yang, Miaoying Shi, et al.
Frontiers in Toxicology (2023) Vol. 5
Open Access | Times Cited: 2

QSAR Models for Predicting ERPG Toxicity Index of Aliphatic Compounds
Xiutang Yuan, Wei Xing Zheng, Jianbo Shi, et al.
Russian Journal of General Chemistry (2024) Vol. 94, Iss. 5, pp. 1167-1178
Closed Access

Chemometric modeling of bioconcentration factor of 6-chloro-1,3,5-triazine derivatives based on MLR-QSPR approach
Milica Karadžić Banjac, Strаhinjа Kоvаčеvić, Sanja Podunavac-Kuzmаnоvić, et al.
Acta periodica technologica (2024), Iss. 55, pp. 203-213
Open Access

Accurate forecasting of bioconcentration factor by incorporating quantum chemical method in the QSAR model
Xiaojie Feng, Jialiang Xiong, Xiao Liu, et al.
Journal of Water Process Engineering (2024) Vol. 68, pp. 106482-106482
Closed Access

BCDPi: An Interpretable Multitask Deep Neural Network Model for Predicting Chemical Bioconcentration in Fish
Zhaoyang Chen, Na Li, Ling Li, et al.
Environmental Research (2024) Vol. 264, pp. 120356-120356
Closed Access

Endocrine disruptor identification and multitoxicity level assessment of organic chemicals: an example of multiple machine learning models
Ning Hao, Yuanyuan Zhao, Peixuan Sun, et al.
Journal of Hazardous Materials (2024) Vol. 485, pp. 136896-136896
Closed Access

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