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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:

Computational Methods for the Discovery of Metabolic Markers of Complex Traits
Michael Y. Lee, Ting Hu
Metabolites (2019) Vol. 9, Iss. 4, pp. 66-66
Open Access | Times Cited: 37

Showing 1-25 of 37 citing articles:

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: 259
Fungal Metabolomics: A Comprehensive Approach to Understanding Pathogenesis in Humans and Identifying Potential Therapeutics
Vinícius Alves, Daniel Zamith‐Miranda, Susana Frasés, et al.
Journal of Fungi (2025) Vol. 11, Iss. 2, pp. 93-93
Open Access | Times Cited: 2
Deep metabolome: Applications of deep learning in metabolomics
Yotsawat Pomyen, Kwanjeera Wanichthanarak, Patcha Poungsombat, et al.
Computational and Structural Biotechnology Journal (2020) Vol. 18, pp. 2818-2825
Open Access | Times Cited: 125
Recent Developments along the Analytical Process for Metabolomics Workflows
Carolina González-Riaño, Danuta Dudzik, Antonia Garcı́a, et al.
Analytical Chemistry (2019) Vol. 92, Iss. 1, pp. 203-226
Closed Access | Times Cited: 84
Metabolomics as a valid analytical technique in environmental exposure research: application and progress
Shuang Wei, Yuanyun Wei, Yaqi Gong, et al.
Metabolomics (2022) Vol. 18, Iss. 6
Closed Access | Times Cited: 25
Harnessing nutrients and natural products for sustainable drug development against aging
Fan Ding, Ying Yu, Yan Zhang, et al.
Frontiers in Pharmacology (2025) Vol. 16
Open Access
Predicting lameness in dairy cattle using untargeted liquid chromatography–mass spectrometry-based metabolomics and machine learning
Laura V. Randall, Dong‐Hyun Kim, Salah M.A. Abdelrazig, et al.
Journal of Dairy Science (2023) Vol. 106, Iss. 10, pp. 7033-7042
Open Access | Times Cited: 9
Metabolomics in Autoimmune Diseases: Focus on Rheumatoid Arthritis, Systemic Lupus Erythematous, and Multiple Sclerosis
Naeun Yoon, Ah-kyung Jang, Yerim Seo, et al.
Metabolites (2021) Vol. 11, Iss. 12, pp. 812-812
Open Access | Times Cited: 23
Discovery of a Metabolic Signature Predisposing High Risk Patients with Mild Cognitive Impairment to Converting to Alzheimer’s Disease
Yi‐Long Huang, Chao‐Hsiung Lin, Tsung‐Hsien Tsai, et al.
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 20, pp. 10903-10903
Open Access | Times Cited: 21
Deep learning analysis of UPLC-MS/MS-based metabolomics data to predict Alzheimer's disease
Kesheng Wang, Laurie A. Theeke, Christopher Liao, et al.
Journal of the Neurological Sciences (2023) Vol. 453, pp. 120812-120812
Open Access | Times Cited: 9
Machine Learning Identifies Metabolic Signatures that Predict the Risk of Recurrent Angina in Remitted Patients after Percutaneous Coronary Intervention: A Multicenter Prospective Cohort Study
Song Cui, Li Li, Yongjiang Zhang, et al.
Advanced Science (2021) Vol. 8, Iss. 10
Open Access | Times Cited: 20
Prospects and challenges of cancer systems medicine: from genes to disease networks
Mohammad Reza Karimi, Amir Hossein Karimi, Shamsozoha Abolmaali, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Open Access | Times Cited: 18
Marine bioactive compounds as antibiofilm agent: a metabolomic approach
Dibyajit Lahiri, Moupriya Nag, Ankita Dey, et al.
Archives of Microbiology (2023) Vol. 205, Iss. 1
Closed Access | Times Cited: 7
Discrimination of rosé wines using shotgun metabolomics with a genetic algorithm and MS ion intensity ratios
Mélodie Gil, Christelle Reynès, Guillaume Cazals, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 20
Evolutionary Computation in bioinformatics: A survey
Yanyun Zhang, Cheng Li, Guanyu Chen, et al.
Neurocomputing (2024) Vol. 591, pp. 127758-127758
Closed Access | Times Cited: 2
Random Forest and Ensemble Methods
George Stavropoulos, Robert van Voorstenbosch, Frederik‐Jan van Schooten, et al.
Elsevier eBooks (2020), pp. 661-672
Closed Access | Times Cited: 17
SMILE: systems metabolomics using interpretable learning and evolution
Chengyuan Sha, Miroslava Čuperlović‐Culf, Ting Hu
BMC Bioinformatics (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 15
Genetic Programming for Interpretable and Explainable Machine Learning
Ting Hu
Genetic and evolutionary computation (2023), pp. 81-90
Closed Access | Times Cited: 6
Coffee authentication via targeted metabolomics and machine learning: Unveiling origins and their discriminating biochemicals
Fawzan Sigma Aurum, Muhammad Zukhrufuz Zaman, Edi Purwanto, et al.
Food Bioscience (2023) Vol. 56, pp. 103122-103122
Closed Access | Times Cited: 6
Feature selection for OPLS discriminant analysis of cancer tissue lipidomics data
Alisa Tokareva, Vitaliy Chagovets, Natalia Starodubtseva, et al.
Journal of Mass Spectrometry (2019) Vol. 55, Iss. 1
Closed Access | Times Cited: 15
Overview of Metabolomic Analysis and the Integration with Multi-Omics for Economic Traits in Cattle
Dan Hao, Jiangsong Bai, Jianyong Du, et al.
Metabolites (2021) Vol. 11, Iss. 11, pp. 753-753
Open Access | Times Cited: 12
Novel Lipid Species for Detecting and Predicting Atrial Fibrillation in Patients With Type 2 Diabetes
Yow Keat Tham, Kaushala S. Jayawardana, Zahir H. Alshehry, et al.
Diabetes (2020) Vol. 70, Iss. 1, pp. 255-261
Open Access | Times Cited: 12
Metabolic network-based identification of plasma markers for non-small cell lung cancer
Linling Guo, Linrui Li, Zhiyun Xu, et al.
Analytical and Bioanalytical Chemistry (2021) Vol. 413, Iss. 30, pp. 7421-7430
Closed Access | Times Cited: 11
The Disruptive 4IR in the Life Sciences: Metabolomics
Fidele Tugizimana, Jasper Engel, Reza M. Salek, et al.
Lecture notes in electrical engineering (2020), pp. 227-256
Closed Access | Times Cited: 11
Can Genetic Programming Perform Explainable Machine Learning for Bioinformatics?
Ting Hu
Genetic and evolutionary computation (2020), pp. 63-77
Closed Access | Times Cited: 9
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