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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:

LC-MS-based lipid profile in colorectal cancer patients: TAGs are the main disturbed lipid markers of colorectal cancer progression
Tong Liu, Feng Peng, Jing Yu, et al.
Analytical and Bioanalytical Chemistry (2019) Vol. 411, Iss. 20, pp. 5079-5088
Closed Access | Times Cited: 41

Showing 1-25 of 41 citing articles:

Sexual Dimorphism in Colon Cancer
Maria Abancens, Viviana Bustos, Harry Harvey, et al.
Frontiers in Oncology (2020) Vol. 10
Open Access | Times Cited: 143
Recent Analytical Methodologies in Lipid Analysis
Ivana Gerhardtová, Timotej Jankech, Petra Majerová, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 4, pp. 2249-2249
Open Access | Times Cited: 18
Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) in disease diagnosis: an overview
Bharath Sampath Kumar
Analytical Methods (2023) Vol. 15, Iss. 31, pp. 3768-3784
Closed Access | Times Cited: 26
The Application of Metabolomics in Recent Colorectal Cancer Studies: A State-of-the-Art Review
Andrew Gold, Fouad Choueiry, Ning Jin, et al.
Cancers (2022) Vol. 14, Iss. 3, pp. 725-725
Open Access | Times Cited: 38
Multi-Omics Approaches in Colorectal Cancer Screening and Diagnosis, Recent Updates and Future Perspectives
Ihsan Ullah, Le Yang, Fengting Yin, et al.
Cancers (2022) Vol. 14, Iss. 22, pp. 5545-5545
Open Access | Times Cited: 37
Prognostic potential of lipid profiling in cancer patients: a systematic review of mass spectrometry-based studies
Yusuke Takanashi, Tomoaki Kahyo, Keigo Sekihara, et al.
Lipids in Health and Disease (2024) Vol. 23, Iss. 1
Open Access | Times Cited: 7
Lipid Metabolism as a Targetable Metabolic Vulnerability in Colorectal Cancer
Yekaterina Y. Zaytseva
Cancers (2021) Vol. 13, Iss. 2, pp. 301-301
Open Access | Times Cited: 38
Lipidomic Signatures for Colorectal Cancer Diagnosis and Progression Using UPLC-QTOF-ESI+MS
Claudiu Răchieriu, Dan Eniu, Emil Moiş, et al.
Biomolecules (2021) Vol. 11, Iss. 3, pp. 417-417
Open Access | Times Cited: 38
Lipid Metabolism Interplay in CRC—An Update
Dana Krauß, Ourania Fari, Maria Sibilia
Metabolites (2022) Vol. 12, Iss. 3, pp. 213-213
Open Access | Times Cited: 25
A conjunctive lipidomic approach reveals plasma ethanolamine plasmalogens and fatty acids as early diagnostic biomarkers for colorectal cancer patients
Tong Liu, Zhi-Rong Tan, Jing Yu, et al.
Expert Review of Proteomics (2020) Vol. 17, Iss. 3, pp. 233-242
Closed Access | Times Cited: 33
Lipidomic landscape in cancer: Actionable insights for membrane‐based therapy and diagnoses
Prema Kumari Agarwala, Ritu Aneja, Shobhna Kapoor
Medicinal Research Reviews (2021) Vol. 42, Iss. 2, pp. 983-1018
Closed Access | Times Cited: 31
Serum untargeted lipidomics by UHPLC-ESI-HRMS aids the biomarker discovery of colorectal adenoma
Hailin Zhou, Yanying Nong, Yifan Zhu, et al.
BMC Cancer (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 20
Establishment of a pseudotargeted LC‒MS/MS workflow for analyzing triglycerides in biological samples
Wei‐Chieh Wang, Chin‐Yi Wang, Ta‐Chen Su, et al.
Analytica Chimica Acta (2025) Vol. 1350, pp. 343874-343874
Closed Access
m6A-induced DEAD-box RNA helicase 21 enhances lipid metabolism via 3‑hydroxy-3-methylglutaryl-CoA synthases 1 in colorectal cancer
Huabin Gao, Shuai Zheng, Jiangtao Liang, et al.
Translational Oncology (2025) Vol. 55, pp. 102373-102373
Closed Access
From Adenoma to Carcinoma: Oxidative Stress and Lipidomic Profile in Colorectal Cancer Patients
Bianca Mihaela Berechet, Olga Orășan, Vasile Negrean, et al.
Journal of Mind and Medical Sciences (2025) Vol. 12, Iss. 1, pp. 16-16
Open Access
Targeting PLA2G16, a lipid metabolism gene, by Ginsenoside Compound K to suppress the malignant progression of colorectal cancer
Li Yang, Lingjie Zheng, Xiao-Nv Xie, et al.
Journal of Advanced Research (2021) Vol. 36, pp. 265-276
Open Access | Times Cited: 27
Lipidomic biomarkers: Potential mediators of associations between urinary bisphenol A exposure and colorectal cancer
Xu Hong, Gengfu Wang, Xingcun Liu, et al.
Journal of Hazardous Materials (2021) Vol. 427, pp. 127863-127863
Closed Access | Times Cited: 24
Metabolic-Dysregulation-Based iEESI-MS Reveals Potential Biomarkers Associated with Early-Stage and Progressive Colorectal Cancer
Ran Zheng, Rui Su, Fan Xing, et al.
Analytical Chemistry (2022) Vol. 94, Iss. 34, pp. 11821-11830
Closed Access | Times Cited: 14
Serum Untargeted UHPLC-HRMS-Based Lipidomics to Discover the Potential Biomarker of Colorectal Advanced Adenoma
Yifan Zhu, Lisheng Wang, Yanying Nong, et al.
Cancer Management and Research (2021) Vol. Volume 13, pp. 8865-8878
Open Access | Times Cited: 16
UHPLC-HRMS–based serum lipisdomics reveals novel biomarkers to assist in the discrimination between colorectal adenoma and cancer
Hongwei Chen, Jiahao Zhang, Hailin Zhou, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 12
The Utility of Lipidomic Analysis in Colorectal Cancer Diagnosis and Prognosis—A Systematic Review of Recent Literature
Jakub Klekowski, Mariusz Chabowski, Małgorzata Krzystek‐Korpacka, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 14, pp. 7722-7722
Open Access | Times Cited: 2
Combining metabolomics and machine learning to discover biomarkers for early-stage breast cancer diagnosis
Nguyen Ky Anh, Anbok Lee, Nguyen Ky Phat, et al.
PLoS ONE (2024) Vol. 19, Iss. 10, pp. e0311810-e0311810
Open Access | Times Cited: 2
A lipid metabolism-related genes prognosis biomarker associated with the tumor immune microenvironment in colorectal carcinoma
Chao Yang, Shuoyang Huang, Fengyu Cao, et al.
BMC Cancer (2021) Vol. 21, Iss. 1
Open Access | Times Cited: 15
Mass spectrometry in the lipid study of cancer
Md. Mahamodun Nabi, Md. Al Mamun, Ariful Islam, et al.
Expert Review of Proteomics (2021) Vol. 18, Iss. 3, pp. 201-219
Closed Access | Times Cited: 15
UHPLC-HRMS-based serum untargeted lipidomics: Phosphatidylcholines and sphingomyelins are the main disturbed lipid markers to distinguish colorectal advanced adenoma from cancer
Hongwei Chen, Hailin Zhou, Yunxiao Liang, et al.
Journal of Pharmaceutical and Biomedical Analysis (2023) Vol. 234, pp. 115582-115582
Closed Access | Times Cited: 6
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