Markus Münz

2.3k total citations · 1 hit paper
18 papers, 1.9k citations indexed

About

Markus Münz is a scholar working on Oncology, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Markus Münz has authored 18 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Oncology, 10 papers in Radiology, Nuclear Medicine and Imaging and 8 papers in Molecular Biology. Recurrent topics in Markus Münz's work include Monoclonal and Polyclonal Antibodies Research (10 papers), CAR-T cell therapy research (6 papers) and Cancer Cells and Metastasis (6 papers). Markus Münz is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (10 papers), CAR-T cell therapy research (6 papers) and Cancer Cells and Metastasis (6 papers). Markus Münz collaborates with scholars based in Germany, United States and Switzerland. Markus Münz's co-authors include Olivier Gires, Patrick A. Baeuerle, Brigitte Mack, C. Kieu, Reinhard Zeidler, Sabine Denzel, Martin Canis, Dorothea Maetzel, Philip Went and Peer Papior and has published in prestigious journals such as PLoS ONE, Nature Cell Biology and Cancer Research.

In The Last Decade

Markus Münz

18 papers receiving 1.8k citations

Hit Papers

Nuclear signalling by tumour-associated antigen EpCAM 2009 2026 2014 2020 2009 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Markus Münz Germany 12 1.0k 1.0k 372 330 269 18 1.9k
Martine L.M. Lamfers Netherlands 33 1.0k 1.0× 1.5k 1.5× 465 1.3× 368 1.1× 147 0.5× 98 2.7k
Isaiah J. Fidler United States 16 750 0.7× 816 0.8× 476 1.3× 296 0.9× 131 0.5× 20 1.7k
Kristopher K. Frese United Kingdom 13 1.2k 1.2× 646 0.6× 460 1.2× 283 0.9× 76 0.3× 13 1.8k
Sandrine Valsesia‐Wittmann France 19 1.5k 1.5× 1.4k 1.3× 479 1.3× 788 2.4× 152 0.6× 24 2.7k
Sara Bobisse Switzerland 19 1000 1.0× 1.1k 1.1× 236 0.6× 667 2.0× 211 0.8× 31 1.8k
Iris Eke Germany 27 886 0.9× 1.0k 1.0× 460 1.2× 173 0.5× 282 1.0× 52 2.1k
Malin Pedersen United Kingdom 22 1.1k 1.0× 1.3k 1.2× 293 0.8× 673 2.0× 126 0.5× 37 2.4k
Shinya Neri Japan 19 1.1k 1.0× 562 0.6× 366 1.0× 341 1.0× 152 0.6× 36 1.7k
Helen Kalirai United Kingdom 25 613 0.6× 847 0.8× 221 0.6× 509 1.5× 256 1.0× 89 1.8k

Countries citing papers authored by Markus Münz

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Markus Münz

This figure shows the co-authorship network connecting the top 25 collaborators of Markus Münz. A scholar is included among the top collaborators of Markus Münz 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 Münz. Markus Münz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Zajc, Charlotte U., Benjamin Salzer, Markus Münz, et al.. (2018). A gB/CD3 bispecific BiTE antibody construct for targeting Human Cytomegalovirus-infected cells. Scientific Reports. 8(1). 17453–17453. 11 indexed citations
2.
Raum, Tobias, et al.. (2015). Impact of Diverse Immune Evasion Mechanisms of Cancer Cells on T Cells Engaged by EpCAM/CD3-Bispecific Antibody Construct AMG 110. PLoS ONE. 10(10). e0141669–e0141669. 20 indexed citations
3.
Münz, Markus. (2014). Funkenerosives Bohren mit großen Aspektverhältnissen. Qucosa (Saxon State and University Library Dresden). 1 indexed citations
4.
Münz, Markus, Alexander Murr, Petra Hoffmann, et al.. (2012). Abstract 4841: Lysis of cancer cells by highly purified T regulatory cells engaged via an EpCAM/CD3-bispecific BiTE antibody. Cancer Research. 72(8_Supplement). 4841–4841. 4 indexed citations
5.
Münz, Markus, Matthias Friedrich, Alexander Murr, et al.. (2011). Abstract 1790: Functional importance of EpCAM for the activity of tumor-initiating cancer cells and their eradication by EpCAM/CD3-bispecific antibody MT110. Cancer Research. 71(8_Supplement). 1790–1790. 2 indexed citations
6.
Rauch, Jens, Eric O’Neill, Brigitte Mack, et al.. (2010). Heterogeneous Nuclear Ribonucleoprotein H Blocks MST2-Mediated Apoptosis in Cancer Cells by Regulating a-raf Transcription. Cancer Research. 70(4). 1679–1688. 65 indexed citations
7.
Baeuerle, Patrick A., Matthias Friedrich, Alexander Murr, et al.. (2010). Highly Efficient Elimination of Colorectal Tumor-Initiating Cells by an EpCAM/CD3-Bispecific Antibody Engaging Human T Cells. PLoS ONE. 5(10). e13474–e13474. 67 indexed citations
8.
Münz, Markus, Alexander Murr, Doris Rau, et al.. (2010). Side-by-side analysis of five clinically tested anti-EpCAM monoclonal antibodies. Cancer Cell International. 10(1). 44–44. 107 indexed citations
9.
Amann, Maria, Grit Lorenczewski, Klaus Brischwein, et al.. (2009). Antitumor Activity of an EpCAM/CD3-bispecific BiTE Antibody During Long-term Treatment of Mice in the Absence of T-cell Anergy and Sustained Cytokine Release. Journal of Immunotherapy. 32(5). 452–464. 43 indexed citations
10.
Maetzel, Dorothea, Sabine Denzel, Brigitte Mack, et al.. (2009). Nuclear signalling by tumour-associated antigen EpCAM. Nature Cell Biology. 11(2). 162–171. 565 indexed citations breakdown →
11.
Münz, Markus, Patrick A. Baeuerle, & Olivier Gires. (2009). The Emerging Role of EpCAM in Cancer and Stem Cell Signaling. Cancer Research. 69(14). 5627–5629. 442 indexed citations
12.
Münz, Markus. (2008). Glycosylation is crucial for stability of tumour and cancer stem cell antigen EpCAM. Frontiers in bioscience. Volume(13). 5195–5195. 60 indexed citations
13.
Zeidler, Reinhard, et al.. (2006). Carcinoma-associated eIF3i overexpression facilitates mTOR-dependent growth transformation. Molecular Carcinogenesis. 45(12). 957–967. 46 indexed citations
14.
Gires, Olivier, et al.. (2005). Targeted gene expression using a 1.1 kilobase promoter fragment of the tumour-associated antigen EpCAM.. PubMed. 24(6). 3715–21. 5 indexed citations
15.
Münz, Markus, C. Kieu, Brigitte Mack, et al.. (2004). The carcinoma-associated antigen EpCAM upregulates c-myc and induces cell proliferation. Oncogene. 23(34). 5748–5758. 295 indexed citations
16.
Münz, Markus, Reinhard Zeidler, & Olivier Gires. (2004). The tumour-associated antigen EpCAM upregulates the fatty acid binding protein E-FABP. Cancer Letters. 225(1). 151–157. 55 indexed citations
17.
Gires, Olivier, et al.. (2003). Cloning and characterisation of a 1.1 kb fragment of the carcinoma-associated epithelial cell adhesion molecule promoter.. PubMed. 23(4). 3255–61. 11 indexed citations
18.
Pauli, Christof, Markus Münz, C. Kieu, et al.. (2003). Tumor-specific glycosylation of the carcinoma-associated epithelial cell adhesion molecule EpCAM in head and neck carcinomas. Cancer Letters. 193(1). 25–32. 77 indexed citations

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.

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