Markus Reischl
- Molecular Biology top 5%
- Biomedical Engineering top 5%
- Cell Biology top 2%
- Physiology top 10%
- Pulmonary and Respiratory Medicine top 10%
- Co-authors
- Ralf MikutRüdiger RudolfChristian PylatiukUrban LiebelSven PernerMuzamil Majid KhanUwe SträhleRüdiger Alshut
- Topics
- Cell Image Analysis Techniques (25 papers)Muscle activation and electromyography studies (22 papers)Zebrafish Biomedical Research Applications (18 papers)
- Journals
- Proceedings of the National Academy of SciencesNature CommunicationsSHILAP Revista de lepidopterología
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Markus Reischl
164 papers receiving 3.3k citations
Peers
Comparison fields: 5 of 181
- Molecular Biology 1.4k
- Biomedical Engineering 497
- Cell Biology 496
- Physiology 290
- Pulmonary and Respiratory Medicine 284
Countries citing papers authored by Markus Reischl
This map shows the geographic impact of Markus Reischl'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 Markus Reischl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Reischl more than expected).
Fields of papers citing papers by Markus Reischl
This network shows the impact of papers produced by Markus Reischl. 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 Markus Reischl. The network helps show where Markus Reischl may publish in the future.
Co-authorship network of co-authors of Markus Reischl
This figure shows the co-authorship network connecting the top 25 collaborators of Markus Reischl. A scholar is included among the top collaborators of Markus Reischl 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 Markus Reischl. Markus Reischl is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 8 | |
| 5 | 2 | |
| 6 | 9 | |
| 7 | 0 | |
| 8 | 10 | |
| 9 | 10 | |
| 10 | 12 | |
| 11 | 5 | |
| 12 | 12 | |
| 13 | 1 | |
| 14 | 17 | |
| 15 | 10 | |
| 16 | 127 | |
| 17 | 54 | |
| 18 | 51 | |
| 19 | 33 | |
| 20 | 17 |
About Markus Reischl
Markus Reischl is a scholar working on Biophysics, Cell Biology and Computer Vision and Pattern Recognition, having authored 186 papers that have together received 3.3k indexed citations. Recurring topics across this work include Cell Image Analysis Techniques (25 papers), Muscle activation and electromyography studies (22 papers) and Zebrafish Biomedical Research Applications (18 papers). The work is most often cited by research in Biophysics (174 citations), Cell Biology (496 citations) and Molecular Biology (1.4k citations). Markus Reischl has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Ralf Mikut, Rüdiger Rudolf, Christian Pylatiuk, Urban Liebel, Sven Perner, Muzamil Majid Khan, Uwe Strähle, Rüdiger Alshut, Ferenc Müller and Pavel A. Levkin. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and SHILAP Revista de lepidopterología.
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.