Stefan Prechtl
Impact in
- Cell Biology top 5%
- Microtubule and mitosis dynamics
- Immunology top 5%
- T-cell and B-cell Immunology
- Immune Cell Function and Interaction
- interferon and immune responses
Papers in
-
- Microtubule and mitosis dynamics 6
- Hippo pathway signaling and YAP/TAZ 1
- Oncology 2
- Drug Transport and Resistance Mechanisms 2
- Co-authors
- Michael D. Lohoff (4 shared papers)David A. Ferrick (2 shared papers)Hans‐Willi Mittrücker (2 shared papers)Gordon S. Duncan (2 shared papers)Tak W. Mak (2 shared papers)Dominik Mumberg (5 shared papers)Gerhard Siemeister (4 shared papers)Martin Röllinghoff (3 shared papers)
- Journals
- Journal of Medicinal Chemistry (2 papers)Experimental Cell Research (2 papers)Journal of Clinical Investigation (1 paper)Combinatorial Chemistry & High Throughput Screening (1 paper)Molecular Cancer Therapeutics (1 paper)
- Partner nations
- GermanyItalyUnited States
In The Last Decade
Stefan Prechtl
17 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 50
- Cell Biology 228
- Immunology 234
- Biophysics 28
- Oncology 100
- Cancer Research 33
Countries citing papers authored by Stefan Prechtl
This map shows the geographic impact of Stefan Prechtl'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 Stefan Prechtl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefan Prechtl more than expected).
Fields of papers citing papers by Stefan Prechtl
This network shows the impact of papers produced by Stefan Prechtl. 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 Stefan Prechtl. The network helps show where Stefan Prechtl may publish in the future.
Co-authors
The 25 scholars most cited alongside Stefan Prechtl, 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 | 2014 | 213 | |
| 2 | 2002 | 204 | |
| 3 | 2007 | 165 | |
| 4 | 2000 | 153 | |
| 5 | 2013 | 98 | |
| 6 | 2016 | 98 | |
| 7 | 2018 | 57 | |
| 8 | 2020 | 41 | |
| 9 | 1998 | 39 | |
| 10 | 2018 | 38 | |
| 11 | 2017 | 35 | |
| 12 | 2000 | 34 | |
| 13 | 2008 | 27 | |
| 14 | 2014 | 21 | |
| 15 | 2015 | 20 | |
| 16 | 2016 | 11 | |
| 17 | 2024 | 7 |
About Stefan Prechtl
Stefan Prechtl is a scholar working on Cell Biology, Oncology, Biophysics, Molecular Biology and Immunology, having authored 17 papers that have together received 1.3k indexed citations. Recurring topics across this work include Microtubule and mitosis dynamics (6 papers), Drug Transport and Resistance Mechanisms (2 papers), Epigenetics and DNA Methylation (1 paper), T-cell and B-cell Immunology (1 paper), Sphingolipid Metabolism and Signaling (1 paper), Hippo pathway signaling and YAP/TAZ (1 paper), Cell Image Analysis Techniques (1 paper) and Melanoma and MAPK Pathways (1 paper). The work is most often cited by research in Cell Biology (228 citations), Immunology (234 citations), Biophysics (28 citations), Oncology (100 citations) and Cancer Research (33 citations). Stefan Prechtl has collaborated with scholars based in Germany, Italy and United States. Frequent co-authors include Michael D. Lohoff, David A. Ferrick, Hans‐Willi Mittrücker, Gordon S. Duncan, Tak W. Mak, Dominik Mumberg, Gerhard Siemeister, Martin Röllinghoff, Volker Schulze and Frank O. Sommer. Their work appears in journals such as Journal of Medicinal Chemistry, Experimental Cell Research, Journal of Clinical Investigation, Combinatorial Chemistry & High Throughput Screening and Molecular Cancer Therapeutics.
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.