Stefan Selbert
Impact in
- Oncology top 10%
- Cytokine Signaling Pathways and Interactions
- Cancer Cells and Metastasis
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- NF-κB Signaling Pathways
Papers in
-
- CRISPR and Genetic Engineering 5
- S100 Proteins and Annexins 3
- Pluripotent Stem Cells Research 3
- DNA Repair Mechanisms 1
- Genetics 4
- Animal Genetics and Reproduction 3
- Virus-based gene therapy research 2
- Co-authors
- Paula C. Lourenco (2 shared papers)Christine J. Watson (2 shared papers)Elizabeth Tonner (2 shared papers)Alan R. Clarke (2 shared papers)Rachel Chapman (2 shared papers)Shizuo Akira (2 shared papers)D. J. Flint (1 shared paper)Kohsuke Takeda (1 shared paper)
- Journals
- The FASEB Journal (1 paper)Journal of Cell Science (1 paper)Cell Biochemistry and Biophysics (1 paper)Transgenic Research (1 paper)Genes & Development (1 paper)
- Partner nations
- GermanyUnited KingdomJapan
In The Last Decade
Stefan Selbert
9 papers receiving 807 citations
Peers
Comparison fields: 5 of 71
- Oncology 341
- Cancer Research 114
- Molecular Biology 479
- Immunology 129
- Genetics 111
Countries citing papers authored by Stefan Selbert
This map shows the geographic impact of Stefan Selbert'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 Selbert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefan Selbert more than expected).
Fields of papers citing papers by Stefan Selbert
This network shows the impact of papers produced by Stefan Selbert. 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 Selbert. The network helps show where Stefan Selbert may publish in the future.
Co-authors
The 25 scholars most cited alongside Stefan Selbert, 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 | 1999 | 393 | |
| 2 | 2000 | 209 | |
| 3 | 1998 | 84 | |
| 4 | 2005 | 64 | |
| 5 | 1995 | 47 | |
| 6 | 1996 | 23 | |
| 7 | 2020 | 3 | |
| 8 | 2003 | 2 | |
| 9 | 2006 | 1 | |
| 10 | 1999 | 0 | |
| 11 | 2002 | 0 |
About Stefan Selbert
Stefan Selbert is a scholar working on Molecular Biology, Genetics, Oncology, Cancer Research and Surgery, having authored 11 papers that have together received 826 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (5 papers), S100 Proteins and Annexins (3 papers), Pluripotent Stem Cells Research (3 papers), Animal Genetics and Reproduction (3 papers), Cytokine Signaling Pathways and Interactions (2 papers), Virus-based gene therapy research (2 papers), DNA Repair Mechanisms (1 paper) and Neuroscience and Neural Engineering (1 paper). The work is most often cited by research in Oncology (341 citations), Cancer Research (114 citations), Molecular Biology (479 citations), Immunology (129 citations) and Genetics (111 citations). Stefan Selbert has collaborated with scholars based in Germany, United Kingdom and Japan. Frequent co-authors include Paula C. Lourenco, Christine J. Watson, Elizabeth Tonner, Alan R. Clarke, Rachel Chapman, Shizuo Akira, D. J. Flint, Kohsuke Takeda, Darren Bentley and J. Hescheler. Their work appears in journals such as The FASEB Journal, Journal of Cell Science, Cell Biochemistry and Biophysics, Transgenic Research and Genes & Development.
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.