Ursula Mayr
- Molecular Biology top 2%
- Cancer Research top 1%
- Cardiology and Cardiovascular Medicine top 5%
- Surgery top 10%
- Immunology top 5%
- Co-authors
- Manuel MayrQingbo XuJohann WilleitStefan KiechlPeter WilleitMarianna ProkopiAnna ZampetakiAjay M. Shah
- Topics
- Metabolomics and Mass Spectrometry Studies (7 papers)Advanced Proteomics Techniques and Applications (7 papers)Angiogenesis and VEGF in Cancer (6 papers)
- Partner nations
- United KingdomGermanyAustria
In The Last Decade
Ursula Mayr
35 papers receiving 3.8k citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Molecular Biology 2.6k
- Cancer Research 1.4k
- Cardiology and Cardiovascular Medicine 612
- Surgery 485
- Immunology 428
Countries citing papers authored by Ursula Mayr
This map shows the geographic impact of Ursula Mayr'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 Ursula Mayr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ursula Mayr more than expected).
Fields of papers citing papers by Ursula Mayr
This network shows the impact of papers produced by Ursula Mayr. 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 Ursula Mayr. The network helps show where Ursula Mayr may publish in the future.
Co-authorship network of co-authors of Ursula Mayr
This figure shows the co-authorship network connecting the top 25 collaborators of Ursula Mayr. A scholar is included among the top collaborators of Ursula Mayr 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 Ursula Mayr. Ursula Mayr is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 6 | |
| 3 | 32 | |
| 4 | Lipidomics Profiling and Risk of Cardiovascular Disease in the Prospective Population-Based Bruneck Studybreakdown → | 418 |
| 5 | 142 | |
| 6 | 27 | |
| 7 | 70 | |
| 8 | 213 | |
| 9 | 179 | |
| 10 | 28 | |
| 11 | 15 | |
| 12 | 148 | |
| 13 | Combined proteomic and metabolomic analysis of vascular smooth muscle cells: role of PKCdelta | 3 |
| 14 | 56 | |
| 15 | 95 | |
| 16 | 190 | |
| 17 | 211 | |
| 18 | The coronary endothelium: a target for vascular endothelial growth factor. Human coronary artery endothelial cells express functional receptors for vascular endothelial growth factor in vitro and in vivo. | 7 |
| 19 | 28 | |
| 20 | 42 |
About Ursula Mayr
Ursula Mayr is a scholar working on Cancer Research, Spectroscopy and Molecular Biology, having authored 35 papers that have together received 3.9k indexed citations. Recurring topics across this work include Metabolomics and Mass Spectrometry Studies (7 papers), Advanced Proteomics Techniques and Applications (7 papers) and Angiogenesis and VEGF in Cancer (6 papers). The work is most often cited by research in Cancer Research (1.4k citations), Molecular Biology (2.6k citations) and Cardiology and Cardiovascular Medicine (612 citations). Ursula Mayr has collaborated with scholars based in United Kingdom, Germany and Austria. Frequent co-authors include Manuel Mayr, Qingbo Xu, Johann Willeit, Stefan Kiechl, Peter Willeit, Marianna Prokopi, Anna Zampetaki, Ajay M. Shah, Ignat Drozdov and Yanhua Hu. Their work appears in journals such as Journal of Biological Chemistry, Circulation and Journal of Clinical Investigation.
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.