Peter V. Treit
Impact in
- Spectroscopy top 2%
- Advanced Proteomics Techniques and Applications
- Mass Spectrometry Techniques and Applications
- Analytical Chemistry and Chromatography
- Health Informatics top 10%
Papers in
-
- Advanced Proteomics Techniques and Applications 7
- Mass Spectrometry Techniques and Applications 2
-
- Machine Learning in Bioinformatics 2
- Glycosylation and Glycoproteins Research 1
- Co-authors
- Philipp E. Geyer (9 shared papers)Matthias Mann (10 shared papers)Sophia Doll (5 shared papers)Johannes Müller (4 shared papers)Lili Niu (3 shared papers)Jakob M. Bader (2 shared papers)Alberto Santos (3 shared papers)Florian Meier (2 shared papers)
- Journals
- Molecular & Cellular Proteomics (4 papers)Molecular Systems Biology (1 paper)EMBO Molecular Medicine (1 paper)Cell Systems (1 paper)Nature (1 paper)
- Partner nations
- GermanyDenmarkUnited Kingdom
In The Last Decade
Peter V. Treit
11 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 124
- Spectroscopy 444
- Health Informatics 20
- Molecular Biology 479
- Cell Biology 79
- Epidemiology 115
Countries citing papers authored by Peter V. Treit
This map shows the geographic impact of Peter V. Treit'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 Peter V. Treit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter V. Treit more than expected).
Fields of papers citing papers by Peter V. Treit
This network shows the impact of papers produced by Peter V. Treit. 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 Peter V. Treit. The network helps show where Peter V. Treit may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter V. Treit, 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 | 2018 | 275 | |
| 2 | 2019 | 211 | |
| 3 | 2019 | 208 | |
| 4 | 2020 | 140 | |
| 5 | 2018 | 74 | |
| 6 | 2023 | 63 | |
| 7 | 2021 | 46 | |
| 8 | 2021 | 27 | |
| 9 | 2021 | 13 | |
| 10 | 2023 | 2 | |
| 11 | 2021 | 1 |
About Peter V. Treit
Peter V. Treit is a scholar working on Spectroscopy, Molecular Biology, Health Informatics, Epidemiology and Public Health, Environmental and Occupational Health, having authored 11 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (7 papers), Mass Spectrometry Techniques and Applications (2 papers), Machine Learning in Bioinformatics (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Ethics in Clinical Research (2 papers), Genomics and Rare Diseases (1 paper), Glycosylation and Glycoproteins Research (1 paper) and Adipose Tissue and Metabolism (1 paper). The work is most often cited by research in Spectroscopy (444 citations), Health Informatics (20 citations), Molecular Biology (479 citations), Cell Biology (79 citations) and Epidemiology (115 citations). Peter V. Treit has collaborated with scholars based in Germany, Denmark and United Kingdom. Frequent co-authors include Philipp E. Geyer, Matthias Mann, Sophia Doll, Johannes Müller, Lili Niu, Jakob M. Bader, Alberto Santos, Florian Meier, Lasse Gaarde Falkenby and Jesper V. Olsen. Their work appears in journals such as Molecular & Cellular Proteomics, Molecular Systems Biology, EMBO Molecular Medicine, Cell Systems and Nature.
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.