Markus Münz
- Oncology top 2%
- CAR-T cell therapy research 6
- Cancer Cells and Metastasis 6
- Cancer Research top 5%
- Biotechnology top 5%
- Immunology top 10%
- Immunotherapy and Immune Responses 3
- Immune Cell Function and Interaction 3
- Molecular Biology top 10%
- Wnt/β-catenin signaling in development and cancer 3
- RNA Research and Splicing 3
- Glycosylation and Glycoproteins Research 2
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- Monoclonal and Polyclonal Antibodies Research 10
- Co-authors
- Olivier GiresPatrick A. BaeuerleBrigitte MackC. KieuReinhard ZeidlerPeer PapiorMartin CanisDorothea Maetzel
- Cited by
- OncologyCancer ResearchBiotechnology
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Markus Münz
18 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 91
- Oncology 1.0k
- Cancer Research 372
- Biotechnology 150
- Immunology 330
- Molecular Biology 1.0k
Countries citing papers authored by Markus Münz
This map shows the geographic impact of Markus Münz'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 Münz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Münz more than expected).
Fields of papers citing papers by Markus Münz
This network shows the impact of papers produced by Markus Münz. 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 Münz. The network helps show where Markus Münz may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Markus Münz, 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 | 2018 | 11 | |
| 2 | 2015 | 20 | |
| 3 | Funkenerosives Bohren mit großen Aspektverhältnissen | 2014 | 1 |
| 4 | 2012 | 4 | |
| 5 | 2011 | 2 | |
| 6 | 2010 | 65 | |
| 7 | 2010 | 107 | |
| 8 | 2010 | 67 | |
| 9 | 2009 | 43 | |
| 10 | Nuclear signalling by tumour-associated antigen EpCAMbreakdown → | 2009 | 565 |
| 11 | 2009 | 442 | |
| 12 | 2008 | 60 | |
| 13 | 2006 | 46 | |
| 14 | Targeted gene expression using a 1.1 kilobase promoter fragment of the tumour-associated antigen EpCAM. | 2005 | 5 |
| 15 | 2004 | 295 | |
| 16 | 2004 | 55 | |
| 17 | 2003 | 77 | |
| 18 | Cloning and characterisation of a 1.1 kb fragment of the carcinoma-associated epithelial cell adhesion molecule promoter. | 2003 | 11 |
About Markus Münz
Markus Münz is a scholar working on Oncology, Radiology, Nuclear Medicine and Imaging and Immunology and Allergy, having authored 18 papers that have together received 1.9k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (10 papers), CAR-T cell therapy research (6 papers), Cancer Cells and Metastasis (6 papers), Immunotherapy and Immune Responses (3 papers), Wnt/β-catenin signaling in development and cancer (3 papers), Immune Cell Function and Interaction (3 papers), RNA Research and Splicing (3 papers) and Glycosylation and Glycoproteins Research (2 papers). The work is most often cited by research in Oncology (1.0k citations), Cancer Research (372 citations) and Biotechnology (150 citations). Markus Münz has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Olivier Gires, Patrick A. Baeuerle, Brigitte Mack, C. Kieu, Reinhard Zeidler, Peer Papior, Martin Canis, Dorothea Maetzel, Sabine Denzel and Philip Went. Their work appears in journals such as Cancer Research, Cancer Letters, PLoS ONE, Molecular Carcinogenesis and Scientific Reports.
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.