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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:

The METLIN small molecule dataset for machine learning-based retention time prediction
Xavier Domingo-Almenara, Carlos Guijas, Elizabeth Billings, et al.
Nature Communications (2019) Vol. 10, Iss. 1
Open Access | Times Cited: 195

Showing 1-25 of 195 citing articles:

DrugBank 6.0: the DrugBank Knowledgebase for 2024
Craig Knox, Michael Wilson, Christen M. Klinger, et al.
Nucleic Acids Research (2023) Vol. 52, Iss. D1, pp. D1265-D1275
Open Access | Times Cited: 485
Machine Learning Applications for Mass Spectrometry-Based Metabolomics
Ulf W. Liebal, An Phan, Malvika Sudhakar, et al.
Metabolites (2020) Vol. 10, Iss. 6, pp. 243-243
Open Access | Times Cited: 266
Spectral entropy outperforms MS/MS dot product similarity for small-molecule compound identification
Yuanyue Li, Tobias Kind, Jacob Folz, et al.
Nature Methods (2021) Vol. 18, Iss. 12, pp. 1524-1531
Closed Access | Times Cited: 139
Taking the leap between analytical chemistry and artificial intelligence: A tutorial review
Lucas B. Ayres, Federico J.V. Gómez, Jeb R. Linton, et al.
Analytica Chimica Acta (2021) Vol. 1161, pp. 338403-338403
Closed Access | Times Cited: 131
Deep learning in analytical chemistry
B. Debus, Hadi Parastar, Peter de B. Harrington, et al.
TrAC Trends in Analytical Chemistry (2021) Vol. 145, pp. 116459-116459
Closed Access | Times Cited: 116
Toward Machine Learning-Enhanced High-Throughput Experimentation
Natalie S. Eyke, Brent A. Koscher, Klavs F. Jensen
Trends in Chemistry (2021) Vol. 3, Iss. 2, pp. 120-132
Open Access | Times Cited: 113
Comprehensive investigation of pathway enrichment methods for functional interpretation of LC–MS global metabolomics data
Yao Lü, Zhiqiang Pang, Jianguo Xia
Briefings in Bioinformatics (2022) Vol. 24, Iss. 1
Open Access | Times Cited: 94
Identification and Prioritization of Environmental Organic Pollutants: From an Analytical and Toxicological Perspective
Ting Ruan, Pengyang Li, Haotian Wang, et al.
Chemical Reviews (2023) Vol. 123, Iss. 17, pp. 10584-10640
Closed Access | Times Cited: 88
Machine learning in preclinical drug discovery
Denise B. Catacutan, Jeremie Alexander, Autumn Arnold, et al.
Nature Chemical Biology (2024) Vol. 20, Iss. 8, pp. 960-973
Closed Access | Times Cited: 45
Explicit relation between thin film chromatography and column chromatography conditions from statistics and machine learning
Hao Xu, Wenchao Wu, Yuntian Chen, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access | Times Cited: 2
Prediction of Chromatographic Retention Time of a Small Molecule from SMILES Representation Using a Hybrid Transformer-LSTM Model
Sargol Mazraedoost, Hadi Sedigh Malekroodi, Petar Žuvela, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access | Times Cited: 2
Recurrent Topics in Mass Spectrometry-Based Metabolomics and Lipidomics—Standardization, Coverage, and Throughput
Evelyn Rampler, Yasin El Abiead, Harald Schoeny, et al.
Analytical Chemistry (2020) Vol. 93, Iss. 1, pp. 519-545
Open Access | Times Cited: 133
Prediction of Analyte Retention Time in Liquid Chromatography
Paul R. Haddad, Maryam Taraji, Roman Szücs
Analytical Chemistry (2020) Vol. 93, Iss. 1, pp. 228-256
Closed Access | Times Cited: 107
Prediction of Liquid Chromatographic Retention Time with Graph Neural Networks to Assist in Small Molecule Identification
Qiong Yang, Hongchao Ji, Hongmei Lü, et al.
Analytical Chemistry (2021) Vol. 93, Iss. 4, pp. 2200-2206
Closed Access | Times Cited: 102
Current status of retention time prediction in metabolite identification
Michael Witting, Sebastian Böcker
Journal of Separation Science (2020) Vol. 43, Iss. 9-10, pp. 1746-1754
Open Access | Times Cited: 100
Integrating multi-omics data for crop improvement
Federico Scossa, Saleh Alseekh, Alisdair R. Fernie
Journal of Plant Physiology (2020) Vol. 257, pp. 153352-153352
Open Access | Times Cited: 98
The Exposome in the Era of One Health
Peng Gao
Environmental Science & Technology (2021) Vol. 55, Iss. 5, pp. 2790-2799
Closed Access | Times Cited: 98
Guide to Semi-Quantitative Non-Targeted Screening Using LC/ESI/HRMS
Louise Malm, Emma Palm, Amina Souihi, et al.
Molecules (2021) Vol. 26, Iss. 12, pp. 3524-3524
Open Access | Times Cited: 88
Exploring new targets and chemical space with affinity selection-mass spectrometry
Renaud Prudent, D. Allen Annis, Peter J. Dandliker, et al.
Nature Reviews Chemistry (2020) Vol. 5, Iss. 1, pp. 62-71
Closed Access | Times Cited: 73
The critical role that spectral libraries play in capturing the metabolomics community knowledge
Wout Bittremieux, Mingxun Wang, Pieter C. Dorrestein
Metabolomics (2022) Vol. 18, Iss. 12
Open Access | Times Cited: 65
Unravelling Plant Responses to Stress—The Importance of Targeted and Untargeted Metabolomics
J. William Allwood, Alex Williams, Henriette Uthe, et al.
Metabolites (2021) Vol. 11, Iss. 8, pp. 558-558
Open Access | Times Cited: 57
Advanced analytical and informatic strategies for metabolite annotation in untargeted metabolomics
Yuping Cai, Zhiwei Zhou, Zheng‐Jiang Zhu
TrAC Trends in Analytical Chemistry (2022) Vol. 158, pp. 116903-116903
Closed Access | Times Cited: 56
BUDDY: molecular formula discovery via bottom-up MS/MS interrogation
Shipei Xing, Sam Shen, Banghua Xu, et al.
Nature Methods (2023) Vol. 20, Iss. 6, pp. 881-890
Open Access | Times Cited: 38
Retention time prediction for chromatographic enantioseparation by quantile geometry-enhanced graph neural network
Hao Xu, Jinglong Lin, Dongxiao Zhang, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 34
RT-Transformer: retention time prediction for metabolite annotation to assist in metabolite identification
Jun Xue, Bingyi Wang, Hongchao Ji, et al.
Bioinformatics (2024) Vol. 40, Iss. 3
Open Access | Times Cited: 17
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