Franziska Tippel
About
In The Last Decade
Franziska Tippel
8 papers receiving 360 citations
Peers
Comparison fields: 5 of 55
- Molecular Biology 333
- Materials Chemistry 69
- Cell Biology 57
- Computational Theory and Mathematics 52
- Immunology 47
Countries citing papers authored by Franziska Tippel
This map shows the geographic impact of Franziska Tippel'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 Franziska Tippel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Franziska Tippel more than expected).
Fields of papers citing papers by Franziska Tippel
This network shows the impact of papers produced by Franziska Tippel. 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 Franziska Tippel. The network helps show where Franziska Tippel may publish in the future.
Co-authorship network of co-authors of Franziska Tippel
This figure shows the co-authorship network connecting the top 25 collaborators of Franziska Tippel. A scholar is included among the top collaborators of Franziska Tippel 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 Franziska Tippel. Franziska Tippel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 29 | |
| 2 | 21 | |
| 3 | 46 | |
| 4 | 32 | |
| 5 | 75 | |
| 6 | 60 | |
| 7 | 69 | |
| 8 | 31 |
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.