Jan C. Refsgaard
Impact in
- Spectroscopy top 10%
- Advanced Proteomics Techniques and Applications
- Mass Spectrometry Techniques and Applications
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- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
Papers in ⓘ
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- Bioinformatics and Genomic Networks 3
- Metabolomics and Mass Spectrometry Studies 3
- Machine Learning in Bioinformatics 1
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- Advanced Proteomics Techniques and Applications 7
- Mass Spectrometry Techniques and Applications 2
- Co-authors
- Lars Juhl Jensen (6 shared papers)Jesper V. Olsen (3 shared papers)Jan Gorodkin (1 shared paper)Alexander Junge (1 shared paper)Morten Rasmussen (1 shared paper)Xiaoyong Pan (1 shared paper)Christopher T. Workman (1 shared paper)Ferhat Alkan (1 shared paper)
- Journals
- Journal of Proteomics (1 paper)Journal of Proteome Research (1 paper)International Journal of Cardiology (1 paper)Bioinformatics (1 paper)Cell (1 paper)
- Partner nations
- DenmarkSwitzerlandNetherlands
In The Last Decade
Jan C. Refsgaard
10 papers receiving 260 citations
Peers
Comparison fields: 5 of 65
- Spectroscopy 76
- Cancer Research 50
- Molecular Biology 192
- Cell Biology 33
- Immunology 12
Countries citing papers authored by Jan C. Refsgaard
This map shows the geographic impact of Jan C. Refsgaard'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 Jan C. Refsgaard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan C. Refsgaard more than expected).
Fields of papers citing papers by Jan C. Refsgaard
This network shows the impact of papers produced by Jan C. Refsgaard. 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 Jan C. Refsgaard. The network helps show where Jan C. Refsgaard may publish in the future.
Co-authors
The 25 scholars most cited alongside Jan C. Refsgaard, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 100 | |
| 2 | 2019 | 62 | |
| 3 | 2011 | 46 | |
| 4 | 2015 | 20 | |
| 5 | 2015 | 11 | |
| 6 | 2015 | 11 | |
| 7 | 2023 | 4 | |
| 8 | 2015 | 4 | |
| 9 | 2019 | 3 | |
| 10 | 2024 | 1 |
About Jan C. Refsgaard
Jan C. Refsgaard is a scholar working on Molecular Biology, Spectroscopy, Cancer Research, Cardiology and Cardiovascular Medicine and Computational Theory and Mathematics, having authored 10 papers that have together received 262 indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (7 papers), Bioinformatics and Genomic Networks (3 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Cancer-related molecular mechanisms research (2 papers), Mass Spectrometry Techniques and Applications (2 papers), Machine Learning in Bioinformatics (1 paper), MicroRNA in disease regulation (1 paper) and Computational Drug Discovery Methods (1 paper). The work is most often cited by research in Spectroscopy (76 citations), Cancer Research (50 citations), Molecular Biology (192 citations), Cell Biology (33 citations) and Immunology (12 citations). Jan C. Refsgaard has collaborated with scholars based in Denmark, Switzerland and Netherlands. Frequent co-authors include Lars Juhl Jensen, Jesper V. Olsen, Jan Gorodkin, Alexander Junge, Morten Rasmussen, Xiaoyong Pan, Christopher T. Workman, Ferhat Alkan, Peng Li and Gunnar Houen. Their work appears in journals such as Journal of Proteomics, Journal of Proteome Research, International Journal of Cardiology, Bioinformatics and Cell.
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.