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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:

Wide spectrum targeted metabolomics identifies potential ovarian cancer biomarkers
Szymon Plewa, Agnieszka Horała, Paweł Dereziński, et al.
Life Sciences (2019) Vol. 222, pp. 235-244
Closed Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

Recent advances in LC‐MS‐based metabolomics for clinical biomarker discovery
Chao‐Jung Chen, Der‐Yen Lee, Jiaxin Yu, et al.
Mass Spectrometry Reviews (2022) Vol. 42, Iss. 6, pp. 2349-2378
Closed Access | Times Cited: 79
Ovarian Cancer Biomarkers: Moving Forward in Early Detection
Vasco D. B. Bonifácio
Advances in experimental medicine and biology (2020), pp. 355-363
Closed Access | Times Cited: 85
WTAP contributes to platinum resistance in high-grade serous ovarian cancer by up-regulating malic acid: insights from liquid chromatography and mass spectrometry analysis
Ming Wang, Shuiqing Xu, Jianqing Xu, et al.
Cancer & Metabolism (2025) Vol. 13, Iss. 1
Open Access | Times Cited: 1
Convergence of Plasma Metabolomics and Proteomics Analysis to Discover Signatures of High-Grade Serous Ovarian Cancer
Hee‐Sung Ahn, Jeonghun Yeom, Jiyoung Yu, et al.
Cancers (2020) Vol. 12, Iss. 11, pp. 3447-3447
Open Access | Times Cited: 39
Plasma-based untargeted metabolomics reveals potential biomarkers for screening and distinguishing of ovarian tumors
Peng Shen, Yiming Zhu, Jing Zhu, et al.
Clinica Chimica Acta (2025), pp. 120246-120246
Closed Access
Serum lipidome screening in patients with stage I non-small cell lung cancer
Agnieszka Klupczyńska, Szymon Plewa, Mariusz Kasprzyk, et al.
Clinical and Experimental Medicine (2019) Vol. 19, Iss. 4, pp. 505-513
Open Access | Times Cited: 39
Emerging Role of Metabolomics in Ovarian Cancer Diagnosis
Asia Saorin, Emanuela Di Gregorio, Gianmaria Miolo, et al.
Metabolites (2020) Vol. 10, Iss. 10, pp. 419-419
Open Access | Times Cited: 37
Pan-cancer analysis of pre-diagnostic blood metabolite concentrations in the European Prospective Investigation into Cancer and Nutrition
Marie Breeur, Pietro Ferrari, Laure Dossus, et al.
BMC Medicine (2022) Vol. 20, Iss. 1
Open Access | Times Cited: 20
Wide-Targeted Metabolome Analysis Identifies Potential Biomarkers for Prognosis Prediction of Epithelial Ovarian Cancer
Eiji Hishinuma, Muneaki Shimada, Naomi Matsukawa, et al.
Toxins (2021) Vol. 13, Iss. 7, pp. 461-461
Open Access | Times Cited: 22
Free Amino Acid Alterations in Patients with Gynecological and Breast Cancer: A Review
Dagmara Pietkiewicz, Agnieszka Klupczyńska, Szymon Plewa, et al.
Pharmaceuticals (2021) Vol. 14, Iss. 8, pp. 731-731
Open Access | Times Cited: 19
Undetectable Free Aromatic Amino Acids in Nails of Breast Carcinoma: Biomarker Discovery by a Novel Metabolite Purification VTGE System
Manmohan Mitruka, Charusheela Gore, Ajay Kumar, et al.
Frontiers in Oncology (2020) Vol. 10
Open Access | Times Cited: 20
The application of metabolomics in ovarian cancer management: a systematic review
Yousra Ahmed-Salim, Nicolas Galazis, Timothy Bracewell‐Milnes, et al.
International Journal of Gynecological Cancer (2020) Vol. 31, Iss. 5, pp. 754-774
Closed Access | Times Cited: 18
Cancer Alters the Metabolic Fingerprint of Extracellular Vesicles
Mari Palviainen, Kirsi Laukkanen, Zeynep Tavukcuoglu, et al.
Cancers (2020) Vol. 12, Iss. 11, pp. 3292-3292
Open Access | Times Cited: 16
Identification and quantification of honeybee venom constituents by multiplatform metabolomics
Agnieszka Klupczyńska, Szymon Plewa, Paweł Dereziński, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 16
Clinical Significance of Screening Differential Metabolites in Ovarian Cancer Tissue and Ascites by LC/MS
Miao Liu, Yu Liu, Hua Feng, et al.
Frontiers in Pharmacology (2021) Vol. 12
Open Access | Times Cited: 14
Applications of Multi-omics Approaches for Exploring the Molecular Mechanism of Ovarian Carcinogenesis
Miaomiao Ye, Yibin Lin, Shuya Pan, et al.
Frontiers in Oncology (2021) Vol. 11
Open Access | Times Cited: 13
Lipid Alterations in Early-Stage High-Grade Serous Ovarian Cancer
Mariia V. Iurova, В. В. Чаговец, Stanislav V. Pavlovich, et al.
Frontiers in Molecular Biosciences (2022) Vol. 9
Open Access | Times Cited: 9
Peripheral Blood Serum NMR Metabolomics Is a Powerful Tool to Discriminate Benign and Malignant Ovarian Tumors
Sofia C. Nunes, Joana Sousa, Fernanda Silva, et al.
Metabolites (2023) Vol. 13, Iss. 9, pp. 989-989
Open Access | Times Cited: 5
Metabolomic Analysis of Amino Acid and Organic Acid Profiles in Tissue From Ovarian Cancer Patients Using High-Performance Liquid Chromatography-Tandem Mass Spectrometry (HPLC-MS/MS) and Gas Chromatography-Tandem Mass Spectrometry (GC-MS/MS)
Songjin Oh, Moongi Ji, Doo-Young Kim, et al.
Analytical Letters (2024), pp. 1-16
Closed Access | Times Cited: 1
Advances in mass spectrometry for metabolomics: Strategies, challenges, and innovations in disease biomarker discovery
Nikhil Titkare, Sachin Chaturvedi, Sapan Borah, et al.
Biomedical Chromatography (2024) Vol. 38, Iss. 12
Open Access | Times Cited: 1
Association of metabolomic markers and response to nutritional support: A secondary analysis of the EFFORT trial using an untargeted metabolomics approach
Tristan Struja, Witold Wolski, Ralph Schapbach, et al.
Clinical Nutrition (2021) Vol. 40, Iss. 9, pp. 5062-5070
Open Access | Times Cited: 10
Untargeted Metabolomic Characterization of Ovarian Tumors
Xiaona Liu, Gang Liu, Lihua Chen, et al.
Cancers (2020) Vol. 12, Iss. 12, pp. 3642-3642
Open Access | Times Cited: 10
Platinum resistance in gynecologic malignancies: Response, disease free and overall survival are predicted by biochemical signature: A metabolomic analysis
Paulo D’Amora, Ismael Dale C. G. Silva, Krishnansu S. Tewari, et al.
Gynecologic Oncology (2021) Vol. 163, Iss. 1, pp. 162-170
Open Access | Times Cited: 9
Machine Learning Reveals Lipidome Remodeling Dynamics in a Mouse Model of Ovarian Cancer
Olatomiwa O. Bifarin, Samyukta Sah, David A. Gaul, et al.
Journal of Proteome Research (2023) Vol. 22, Iss. 6, pp. 2092-2108
Open Access | Times Cited: 3
Metabolome Sequencing Reveals that Protein Arginine-N-Methyltransferase 1 Promotes the Progression of Invasive Micropapillary Carcinoma of the Breast and Predicts a Poor Prognosis
K Wu, Weidong Li, Hanjiao Liu, et al.
American Journal Of Pathology (2023) Vol. 193, Iss. 9, pp. 1267-1283
Open Access | Times Cited: 3
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