Markus Rempfler
Impact in
- Cell Biology top 10%
- Cellular Mechanics and Interactions
- Hippo pathway signaling and YAP/TAZ
- Biophysics top 5%
- Cell Image Analysis Techniques
Papers in
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- Medical Image Segmentation Techniques 4
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- Single-cell and spatial transcriptomics 2
- Co-authors
- Prisca Liberali (2 shared papers)Michael Stadler (1 shared paper)Denise Serra (1 shared paper)Guglielmo Roma (1 shared paper)Panagiotis Papasaikas (1 shared paper)Andrea Boni (1 shared paper)Annick Waldt (1 shared paper)Ludivine Challet Meylan (1 shared paper)
- Journals
- Medical Image Analysis (2 papers)Nature (1 paper)Radiology Artificial Intelligence (1 paper)Nucleic Acids Research (1 paper)The EMBO Journal (1 paper)
- Partner nations
- GermanySwitzerlandUnited States
In The Last Decade
Markus Rempfler
12 papers receiving 600 citations
Markus Rempfler's Hit Papers
Peers
Comparison fields: 5 of 93
- Cell Biology 184
- Biophysics 49
- Oncology 203
- Aging 13
- Biomedical Engineering 216
Countries citing papers authored by Markus Rempfler
This map shows the geographic impact of Markus Rempfler'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 Rempfler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Rempfler more than expected).
Fields of papers citing papers by Markus Rempfler
This network shows the impact of papers produced by Markus Rempfler. 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 Rempfler. The network helps show where Markus Rempfler may publish in the future.
Co-authors
The 25 scholars most cited alongside Markus Rempfler, 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 | Self-organization and symmetry breaking in intestinal organoid development Hit paper breakdown → | 2019 | 375 |
| 2 | 2021 | 115 | |
| 3 | 2020 | 31 | |
| 4 | 2021 | 25 | |
| 5 | 2015 | 16 | |
| 6 | 2023 | 13 | |
| 7 | 2018 | 12 | |
| 8 | 2014 | 5 | |
| 9 | 2016 | 5 | |
| 10 | 2016 | 3 | |
| 11 | 2017 | 3 | |
| 12 | Adversarially Learning a Local Anatomical Prior: Vertebrae Labelling with 2D reformations. | 2019 | 2 |
About Markus Rempfler
Markus Rempfler is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology, Biophysics, Oncology and Cell Biology, having authored 12 papers that have together received 605 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (4 papers), Cell Image Analysis Techniques (4 papers), Hippo pathway signaling and YAP/TAZ (2 papers), Medical Imaging and Analysis (2 papers), Single-cell and spatial transcriptomics (2 papers), Cancer Cells and Metastasis (2 papers), AI in cancer detection (1 paper) and Circadian rhythm and melatonin (1 paper). The work is most often cited by research in Cell Biology (184 citations), Biophysics (49 citations), Oncology (203 citations), Aging (13 citations) and Biomedical Engineering (216 citations). Markus Rempfler has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include Prisca Liberali, Michael Stadler, Denise Serra, Guglielmo Roma, Panagiotis Papasaikas, Andrea Boni, Annick Waldt, Ludivine Challet Meylan, Ilya Lukonin and Urs Mayr. Their work appears in journals such as Medical Image Analysis, Nature, Radiology Artificial Intelligence, Nucleic Acids Research and The EMBO Journal.
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.