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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 of molecular representation in the age of machine learning
Daniel Wigh, Jonathan M. Goodman, Alexei A. Lapkin
Wiley Interdisciplinary Reviews Computational Molecular Science (2022) Vol. 12, Iss. 5
Open Access | Times Cited: 180

Showing 26-50 of 180 citing articles:

Advances in machine learning screening of food bioactive compounds
Yiyun Zhang, Xin Bao, Yiqing Zhu, et al.
Trends in Food Science & Technology (2024) Vol. 150, pp. 104578-104578
Closed Access | Times Cited: 6
A novel approach to unlocking the synergy of large language models and chemical knowledge in biomedical signal applications
Zilong Yin, Haoyu Wang, Bin Chen, et al.
Biomedical Signal Processing and Control (2025) Vol. 103, pp. 107388-107388
Closed Access
Molecular dynamics and machine learning unlock possibilities in beauty design—A perspective
Yuzhi Xu, Haowei Ni, Fanyu Zhao, et al.
AIP Advances (2025) Vol. 15, Iss. 1
Open Access
Chemical space as a unifying theme for chemistry
Jean‐Louis Reymond
Journal of Cheminformatics (2025) Vol. 17, Iss. 1
Open Access
Computational tools for handling large databases of biological relevance
Nicolás Aparicio, Paula Cárdenas, Juanita Puentes, et al.
Elsevier eBooks (2025), pp. 81-96
Closed Access
Machine Learning-Guided Space-filling Designs for High Throughput Liquid Formulation Development
Aniket Chitre, Daria Semochkina, David C. Woods, et al.
Computers & Chemical Engineering (2025), pp. 109007-109007
Open Access
Harnessing AI for Enhanced Screening of Antimicrobial Bioactive Compounds in Food Safety and Preservation
Mengyue Zhou, Juliana Pinto de Lima, Hefei Zhao, et al.
Trends in Food Science & Technology (2025), pp. 104887-104887
Closed Access
Guiding the rational design of biocompatible metal-organic frameworks for drug delivery
Dhruv Menon, David Fairen‐Jimenez
Matter (2025), pp. 101958-101958
Open Access
PPARγ modulator predictor (PGMP_v1): chemical space exploration and computational insights for enhanced type 2 diabetes mellitus management
Sk. Abdul Amin, Lucia Sessa, Shovanlal Gayen, et al.
Molecular Diversity (2025)
Closed Access
Molecular Dynamics (MD)-Derived Features for Canonical and Noncanonical Amino Acids
Tiffani Hui, Maxim Secor, Minh Ngoc Ho, et al.
Journal of Chemical Information and Modeling (2025)
Open Access
Machine Learning in Polymer Research
Wei Ge, R. Silva‐González, Yanan Fan, et al.
Advanced Materials (2025)
Open Access
Bridging Chemical Knowledge and Machine Learning for Performance Prediction of Organic Synthesis
Shuo‐Qing Zhang, Li‐Cheng Xu, Shu‐Wen Li, et al.
Chemistry - A European Journal (2022) Vol. 29, Iss. 6
Open Access | Times Cited: 26
From intuition to AI: evolution of small molecule representations in drug discovery
Miles McGibbon, Steven Shave, Jie Dong, et al.
Briefings in Bioinformatics (2023) Vol. 25, Iss. 1
Open Access | Times Cited: 17
De novo drug design through artificial intelligence: an introduction
Davide Crucitti, Carlos Pérez Míguez, José Ángel Díaz Arias, et al.
Frontiers in Hematology (2024) Vol. 3
Open Access | Times Cited: 5
Multimodal fused deep learning for drug property prediction: Integrating chemical language and molecular graph
Xiaohua Lu, Liangxu Xie, Lei Xu, et al.
Computational and Structural Biotechnology Journal (2024) Vol. 23, pp. 1666-1679
Open Access | Times Cited: 5
Carbon-based molecular properties efficiently predicted by deep learning-based quantum chemical simulation with large language models
Haoyu Wang, Bin Chen, Hangling Sun, et al.
Computers in Biology and Medicine (2024) Vol. 176, pp. 108531-108531
Closed Access | Times Cited: 5
Advances in machine learning with chemical language models in molecular property and reaction outcome predictions
Manajit Das, Ankit Ghosh, Raghavan B. Sunoj
Journal of Computational Chemistry (2024) Vol. 45, Iss. 14, pp. 1160-1176
Closed Access | Times Cited: 4
Artificial intelligence in antidiabetic drug discovery: The advances in QSAR and the prediction of α-glucosidase inhibitors
Adeshina I. Odugbemi, Clement N. Nyirenda, Alan Christoffels, et al.
Computational and Structural Biotechnology Journal (2024) Vol. 23, pp. 2964-2977
Open Access | Times Cited: 4
Automated pH Adjustment Driven by Robotic Workflows and Active Machine Learning
Alexander Pomberger, Nicholas A. Jose, D. Walz, et al.
Chemical Engineering Journal (2022) Vol. 451, pp. 139099-139099
Open Access | Times Cited: 23
Recent Applications of Machine Learning in Molecular Property and Chemical Reaction Outcome Predictions
Shilpa Shilpa, Gargee Kashyap, Raghavan B. Sunoj
The Journal of Physical Chemistry A (2023) Vol. 127, Iss. 40, pp. 8253-8271
Closed Access | Times Cited: 14
Artificial Intelligence in Material Engineering: A Review on Applications of Artificial Intelligence in Material Engineering
Lipichanda Goswami, Manoj Kumar Deka, Mohendra Roy
Advanced Engineering Materials (2023) Vol. 25, Iss. 13
Open Access | Times Cited: 13
Harnessing Shannon entropy-based descriptors in machine learning models to enhance the prediction accuracy of molecular properties
Rajarshi Guha, Darrell Velegol
Journal of Cheminformatics (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 12
Perspective: use and reuse of NMR-based metabolomics data: what works and what remains challenging
Gonçalo J. Gouveia, Thomas C. Head, Leo L. Cheng, et al.
Metabolomics (2024) Vol. 20, Iss. 2
Closed Access | Times Cited: 4
Application of ensemble learning for predicting GABAA receptor agonists
Xiao Fu, Xiaoyu Ding, Yan Shi, et al.
Computers in Biology and Medicine (2024) Vol. 169, pp. 107958-107958
Closed Access | Times Cited: 3
Improving chemical reaction yield prediction using pre-trained graph neural networks
Jongmin Han, Youngchun Kwon, Youn-Suk Choi, et al.
Journal of Cheminformatics (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 3

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