Oleg A. Mayboroda

5.5k total citations
128 papers, 4.3k citations indexed

About

Oleg A. Mayboroda is a scholar working on Molecular Biology, Spectroscopy and Biomedical Engineering. According to data from OpenAlex, Oleg A. Mayboroda has authored 128 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 87 papers in Molecular Biology, 29 papers in Spectroscopy and 16 papers in Biomedical Engineering. Recurrent topics in Oleg A. Mayboroda's work include Metabolomics and Mass Spectrometry Studies (47 papers), Mass Spectrometry Techniques and Applications (21 papers) and Glycosylation and Glycoproteins Research (15 papers). Oleg A. Mayboroda is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (47 papers), Mass Spectrometry Techniques and Applications (21 papers) and Glycosylation and Glycoproteins Research (15 papers). Oleg A. Mayboroda collaborates with scholars based in Netherlands, Russia and Germany. Oleg A. Mayboroda's co-authors include André M. Deelder, Rawi Ramautar, Martin Giera, Alegría Carrasco‐Pancorbo, Rico J. E. Derks, Manfred Wuhrer, Ekaterina Nevedomskaya, Jean‐Marc Busnel, Tiziana Pacchiarotta and Alberto Fernández‐Gutiérrez and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and The Journal of Cell Biology.

In The Last Decade

Oleg A. Mayboroda

126 papers receiving 4.2k citations

Peers

Oleg A. Mayboroda
Leesa J. Deterding United States
Andrew R. Pitt United Kingdom
Stephen Naylor United States
M. Arthur Moseley United States
Wayne F. Patton United States
Johannes P.C. Vissers United Kingdom
Tao Liu United States
Leesa J. Deterding United States
Oleg A. Mayboroda
Citations per year, relative to Oleg A. Mayboroda Oleg A. Mayboroda (= 1×) peers Leesa J. Deterding

Countries citing papers authored by Oleg A. Mayboroda

Since Specialization
Citations

This map shows the geographic impact of Oleg A. Mayboroda's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Oleg A. Mayboroda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Oleg A. Mayboroda more than expected).

Fields of papers citing papers by Oleg A. Mayboroda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Oleg A. Mayboroda. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Oleg A. Mayboroda. The network helps show where Oleg A. Mayboroda may publish in the future.

Co-authorship network of co-authors of Oleg A. Mayboroda

This figure shows the co-authorship network connecting the top 25 collaborators of Oleg A. Mayboroda. A scholar is included among the top collaborators of Oleg A. Mayboroda based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Oleg A. Mayboroda. Oleg A. Mayboroda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Madunić, Katarina, et al.. (2024). (Sialyl)Lewis Antigen Expression on Glycosphingolipids, N-, and O-Glycans in Colorectal Cancer Cell Lines is Linked to a Colon-Like Differentiation Program. Molecular & Cellular Proteomics. 23(6). 100776–100776. 6 indexed citations
2.
Madunić, Katarina, et al.. (2023). In-Depth Analysis of the N-Glycome of Colorectal Cancer Cell Lines. International Journal of Molecular Sciences. 24(5). 4842–4842. 4 indexed citations
3.
Mayboroda, Oleg A., Guinevere S. M. Lageveen‐Kammeijer, Manfred Wuhrer, & Radboud J. E. M. Dolhain. (2023). An Integrated Glycosylation Signature of Rheumatoid Arthritis. Biomolecules. 13(7). 1106–1106. 10 indexed citations
4.
Köhler, Isabelle, Aswin Verhoeven, Rico J. E. Derks, et al.. (2022). Urinary Metabolic Profiling in Volunteers Undergoing Malaria Challenge in Gabon. Metabolites. 12(12). 1224–1224. 2 indexed citations
5.
Verhoeven, Aswin, et al.. (2022). Change in Urinary Myoinositol/Citrate Ratio Associates with Progressive Loss of Renal Function in ADPKD Patients. American Journal of Nephrology. 53(6). 470–480. 5 indexed citations
6.
Kostidis, Sarantos, et al.. (2021). Metabolic Reprogramming of Mammary Epithelial Cells during TGF-β-Induced Epithelial-to-Mesenchymal Transition. Metabolites. 11(9). 626–626. 13 indexed citations
7.
Vrieling, Frank, Sarantos Kostidis, Herman P. Spaink, et al.. (2020). Analyzing the impact of Mycobacterium tuberculosis infection on primary human macrophages by combined exploratory and targeted metabolomics. Scientific Reports. 10(1). 7085–7085. 32 indexed citations
8.
Sánchez‐López, Elena, H. Kevin Happe, Evelyne Steenvoorden, et al.. (2017). A cross-platform metabolomics workflow for volume-restricted tissue samples: application to an animal model for polycystic kidney disease. Molecular BioSystems. 13(10). 1940–1945. 3 indexed citations
9.
Verhoeven, Aswin, P. Eline Slagboom, Manfred Wuhrer, Martin Giera, & Oleg A. Mayboroda. (2017). Automated quantification of metabolites in blood-derived samples by NMR. Analytica Chimica Acta. 976. 52–62. 21 indexed citations
10.
Zielman, Ronald, Aswin Verhoeven, F. Bakels, et al.. (2016). Metabolomic changes in CSF of migraine patients measured with 1H-NMR spectroscopy. Molecular BioSystems. 12(12). 3674–3682. 13 indexed citations
11.
Kooten, Cees van, et al.. (2016). ER Stress and Loss of GRP78 Expression Provides a Link Between Renal Ischemia/Reperfusion Injury and the Urinary Metabolome. American Journal of Transplantation. 16. 638–638. 3 indexed citations
12.
Schaapherder, Alexander F., Dorottya K. de Vries, Lars Verschuren, et al.. (2016). Defective postreperfusion metabolic recovery directly associates with incident delayed graft function. Kidney International. 90(1). 181–191. 31 indexed citations
13.
Shyti, Reinald, Isabelle Köhler, Bart Schoenmaker, et al.. (2015). Plasma metabolic profiling after cortical spreading depression in a transgenic mouse model of hemiplegic migraine by capillary electrophoresis – mass spectrometry. Molecular BioSystems. 11(5). 1462–1471. 21 indexed citations
14.
Ramautar, Rawi, Anthonius A. M. Heemskerk, Paul J. Hensbergen, et al.. (2012). CE–MS for proteomics: Advances in interface development and application. Journal of Proteomics. 75(13). 3814–3828. 62 indexed citations
15.
Nevedomskaya, Ekaterina, Oleg A. Mayboroda, & André M. Deelder. (2011). Cross-platform analysis of longitudinal data in metabolomics. Molecular BioSystems. 7(12). 3214–3222. 19 indexed citations
16.
Balog, Crina I.A., Axel Meißner, Marco R. Bladergroen, et al.. (2011). Metabonomic investigation of human Schistosoma mansoni infection. Molecular BioSystems. 7(5). 1473–1480. 53 indexed citations
17.
Giera, Martin, et al.. (2011). Mild and selective labeling of malondialdehyde with 2-aminoacridone: assessment of urinary malondialdehyde levels. The Analyst. 136(13). 2763–2763. 19 indexed citations
18.
Ramautar, Rawi, Ekaterina Nevedomskaya, Oleg A. Mayboroda, et al.. (2010). Metabolic profiling of human urine by CE-MS using a positively charged capillary coating and comparison with UPLC-MS. Molecular BioSystems. 7(1). 194–199. 44 indexed citations
19.
Carrasco‐Pancorbo, Alegría, Ekaterina Nevedomskaya, Tiziana Pacchiarotta, et al.. (2010). GC/APCI-TOF MS: A New Valuable Tool for Analysis of Biofluids in Metabolomics Studies. Journal of Biomolecular Techniques JBT. 21. 3 indexed citations
20.
Dumler, Inna, Oleg A. Mayboroda, Uwe Jerke, et al.. (1999). Urokinase Induces Activation and Formation of Stat4 and Stat1-Stat2 Complexes in Human Vascular Smooth Muscle Cells. Journal of Biological Chemistry. 274(34). 24059–24065. 40 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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