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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:

A Review on the Recent Applications of Deep Learning in Predictive Drug Toxicological Studies
Krishnendu Sinha, Nabanita Ghosh, Parames C. Sil
Chemical Research in Toxicology (2023) Vol. 36, Iss. 8, pp. 1174-1205
Closed Access | Times Cited: 22

Showing 22 citing articles:

Machine learning in toxicological sciences: opportunities for assessing drug toxicity
Lusine Tonoyan, Arno G. Siraki
Frontiers in Drug Discovery (2024) Vol. 4
Open Access | Times Cited: 7
Network pharmacology and molecular docking: combined computational approaches to explore the antihypertensive potential of Fabaceae species
Zainab Shahzadi, Zubaida Yousaf, İrfan Anjum, et al.
Bioresources and Bioprocessing (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 6
A deep learning based multi-model approach for predicting drug-like chemical compound’s toxicity
Konda Mani Saravanan, Jiang-Fan Wan, Liujiang Dai, et al.
Methods (2024) Vol. 226, pp. 164-175
Closed Access | Times Cited: 5
A review of transformers in drug discovery and beyond
Jian Jiang, Long Chen, Ke Lü, et al.
Journal of Pharmaceutical Analysis (2024), pp. 101081-101081
Open Access | Times Cited: 5
The recent advances in the approach of artificial intelligence (AI) towards drug discovery
Mahroza Kanwal Khan, Mohsin Ali Raza, Muhammad Shahbaz, et al.
Frontiers in Chemistry (2024) Vol. 12
Open Access | Times Cited: 4
Deep learning: A game changer in drug design and development
Sushanta Kumar Das, Rahul Mishra, Amit Samanta, et al.
Advances in pharmacology (2025)
Closed Access
A small-scale data driven and graph neural network based toxicity prediction method of compounds
Xin Zhao, Shuyi Zhang, Tao Zhang, et al.
Computational Biology and Chemistry (2025) Vol. 117, pp. 108393-108393
Closed Access
Binding Affinity Prediction and Pesticide Screening against Phytophthora sojae Using a Heterogeneous Interaction Graph Attention Network–Based Model
Youxu Dai, Aiping Han, Hui-Jun Ma, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access
Analysis of gene regulatory networks from gene expression using graph neural networks
Hakan T. Otal, Abdülhamit Subaşı, Furkan Kurt, et al.
Elsevier eBooks (2025), pp. 249-270
Closed Access
Classification and regression machine learning models for predicting mixed toxicity of carbamazepine and its transformation products
Xiaohan Huang, Haoran Wang, Zujian Wu, et al.
Environmental Research (2025), pp. 121089-121089
Closed Access
Computational methods and key considerations for in silico design of proteolysis targeting chimera (PROTACs)
Amr E. Abbas, Fei Ye
International Journal of Biological Macromolecules (2024) Vol. 277, pp. 134293-134293
Closed Access | Times Cited: 3
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: 7
A Comparative Study of Deep Learning Models and Classification Algorithms for Chemical Compound Identification and Tox21 Prediction
Yusuf Alaca, Berkay Emi̇n, Akif Akgül
Computers & Chemical Engineering (2024) Vol. 189, pp. 108805-108805
Closed Access | Times Cited: 2
The dark side of beauty: an in-depth analysis of the health hazards and toxicological impact of synthetic cosmetics and personal care products
Abdullah M. Alnuqaydan
Frontiers in Public Health (2024) Vol. 12
Open Access | Times Cited: 2
FGTN: Fragment-based graph transformer network for predicting reproductive toxicity
Jia-Nan Ren, Qiang Chen, Hong-Yu-Xiang Ye, et al.
Archives of Toxicology (2024)
Closed Access | Times Cited: 2
Using the Super-learner to Predict the Chemical Acute Toxicity on Rats
Yuzhe Li, Bixuan Wang, Fujun Ma, et al.
Journal of Hazardous Materials (2024) Vol. 480, pp. 136311-136311
Closed Access | Times Cited: 2
Analysis of metabolites in human gut: illuminating the design of gut-targeted drugs
Alberto Gil-Pichardo, Andrés Sánchez-Ruiz, Gonzalo Colmenarejo
Journal of Cheminformatics (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 4
TPepPro: a deep learning model for predicting peptide-protein interactions
Jin Xiao-hong, Zimeng Chen, Dan Yu, et al.
Bioinformatics (2024) Vol. 41, Iss. 1
Open Access | Times Cited: 1
Exploring Antibiotic Resistance Through Artificial Intelligence: A Novel Perspective
D Kalyani, Rompicharla Narasimha Sai, K Somasekhar Reddy, et al.
UTTAR PRADESH JOURNAL OF ZOOLOGY (2024) Vol. 45, Iss. 11, pp. 203-217
Open Access
Fast prediction of optimal reaction conditions and dyeing effects of natural dyes on silk fabrics by lightweight integrated learning (XGBoost) models
Jie Chen, Yuyang Lin, Ying Liu
Coloration Technology (2024)
Closed Access
A Brief Guide to Big Data in Molecular Design: From Concepts and Definitions to Models
Jarosław Polański
(2023)
Open Access | Times Cited: 1
Revolutionizing Drug Discovery: The Role of AI and Machine Learning
Abhinav Vashishat, Ghanshyam Das Gupta, Balak Das Kurmi
Current Pharmaceutical Design (2023) Vol. 29, Iss. 39, pp. 3087-3088
Closed Access
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