Kurt S. Zänker

8.1k total citations
148 papers, 6.1k citations indexed

About

Kurt S. Zänker is a scholar working on Oncology, Molecular Biology and Immunology. According to data from OpenAlex, Kurt S. Zänker has authored 148 papers receiving a total of 6.1k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Oncology, 56 papers in Molecular Biology and 32 papers in Immunology. Recurrent topics in Kurt S. Zänker's work include Cancer Cells and Metastasis (37 papers), Cell Adhesion Molecules Research (27 papers) and Cellular Mechanics and Interactions (21 papers). Kurt S. Zänker is often cited by papers focused on Cancer Cells and Metastasis (37 papers), Cell Adhesion Molecules Research (27 papers) and Cellular Mechanics and Interactions (21 papers). Kurt S. Zänker collaborates with scholars based in Germany, Croatia and United Kingdom. Kurt S. Zänker's co-authors include Bernd Niggemann, Peter Friedl, Frank Entschladen, Thomas Dittmar, Burkhard Brandt, Frank Gebhardt, Eva‐B. Bröcker, Peter B. Noble, Kerstin Lang and Matthias Gunzer and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Oncology.

In The Last Decade

Kurt S. Zänker

147 papers receiving 6.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kurt S. Zänker Germany 40 2.2k 2.1k 1.3k 1.2k 995 148 6.1k
Lynne‐Marie Postovit Canada 40 1.8k 0.8× 3.5k 1.6× 670 0.5× 796 0.7× 1.1k 1.1× 110 6.0k
Burt Nabors United States 52 2.3k 1.0× 4.2k 1.9× 1.2k 0.9× 329 0.3× 2.0k 2.0× 267 9.5k
Howard C. Crawford United States 56 5.0k 2.3× 5.4k 2.5× 1.8k 1.4× 871 0.7× 2.8k 2.8× 139 11.0k
Stuart S. Martin United States 42 1.6k 0.7× 2.5k 1.2× 441 0.4× 1.4k 1.2× 803 0.8× 109 4.8k
Enrico Crivellato Italy 43 870 0.4× 2.3k 1.1× 1.9k 1.5× 527 0.4× 542 0.5× 172 5.5k
Ole Didrik Lærum Norway 42 1.3k 0.6× 2.0k 0.9× 643 0.5× 591 0.5× 941 0.9× 200 5.3k
Johan Kreuger Sweden 28 931 0.4× 4.1k 1.9× 593 0.5× 2.0k 1.6× 920 0.9× 57 6.3k
Richard Meyermann Germany 55 1.4k 0.6× 3.5k 1.6× 2.7k 2.2× 353 0.3× 1.2k 1.2× 242 11.1k
Michael F. Olson United Kingdom 46 2.4k 1.1× 6.9k 3.2× 1.4k 1.1× 3.5k 2.9× 1.1k 1.1× 132 10.7k
Brad St. Croix United States 32 1.8k 0.8× 4.1k 1.9× 761 0.6× 697 0.6× 1.4k 1.4× 58 6.0k

Countries citing papers authored by Kurt S. Zänker

Since Specialization
Citations

This map shows the geographic impact of Kurt S. Zänker'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 Kurt S. Zänker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kurt S. Zänker more than expected).

Fields of papers citing papers by Kurt S. Zänker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kurt S. Zänker. 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 Kurt S. Zänker. The network helps show where Kurt S. Zänker may publish in the future.

Co-authorship network of co-authors of Kurt S. Zänker

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

All Works

20 of 20 papers shown
1.
Hengstler, Jan G., et al.. (2018). β-Heregulin impairs EGF induced PLC-γ1 signalling in human breast cancer cells. Cellular Signalling. 52. 23–34. 4 indexed citations
2.
Zänker, Kurt S., et al.. (2018). Matrix metalloproteinase-9 (MMP9) is involved in the TNF-α-induced fusion of human M13SV1-Cre breast epithelial cells and human MDA-MB-435-pFDR1 cancer cells. Cell Communication and Signaling. 16(1). 14–14. 37 indexed citations
3.
Kurgyis, Zsuzsanna, et al.. (2016). Melanoma Cells Can Adopt the Phenotype of Stromal Fibroblasts and Macrophages by Spontaneous Cell Fusion in Vitro. International Journal of Molecular Sciences. 17(6). 826–826. 27 indexed citations
4.
Edlund, Karolina, Marianna Grinberg, Seddik Hammad, et al.. (2015). Gelsolin Is Associated with Longer Metastasis-free Survival and Reduced Cell Migration in Estrogen Receptor-positive Breast Cancer.. PubMed. 35(10). 5277–85. 16 indexed citations
5.
Dittmar, Thomas & Kurt S. Zänker. (2015). Tissue Regeneration in the Chronically Inflamed Tumor Environment: Implications for Cell Fusion Driven Tumor Progression and Therapy Resistant Tumor Hybrid Cells. International Journal of Molecular Sciences. 16(12). 30362–30381. 28 indexed citations
6.
Assenmacher, Mario, et al.. (2013). Multiplex and functional detection of antigen-specific human T cells by ITRA—Indirect T cell recognition assay. Journal of Immunological Methods. 404. 13–23. 3 indexed citations
7.
Bartkowiak, Kai, Antje Andreas, Klaus Pantel, et al.. (2012). The interplay of HER2/HER3/PI3K and EGFR/HER2/PLC ‐γ 1 signalling in breast cancer cell migration and dissemination. The Journal of Pathology. 227(2). 234–244. 76 indexed citations
8.
Brandt, Burkhard, et al.. (2012). Hybrid cells derived from breast epithelial cell/breast cancer cell fusion events show a differential RAF-AKT crosstalk. Cell Communication and Signaling. 10(1). 10–10. 33 indexed citations
9.
Zänker, Kurt S., et al.. (2011). Cell Fusion, Drug Resistance and Recurrence CSCs. Advances in experimental medicine and biology. 714. 173–182. 38 indexed citations
10.
Dittmar, Thomas & Kurt S. Zänker. (2011). Cell fusion in disease. Springer eBooks. 1 indexed citations
11.
12.
Schwitalla, Sarah, et al.. (2007). VISCUM ALBUM EXTRACTS ISCADOR ® P AND ISCADOR ® M COUNTERACT THE GROWTH FACTOR INDUCED EFFECTS IN HUMAN FOLLICULAR B-NHL CELLS AND BREAST CANCER CELLS. Medicina-buenos Aires. 67. 90–96. 5 indexed citations
13.
Diederichs, Sven, Etmar Bulk, Björn Steffen, et al.. (2004). S100 Family Members and Trypsinogens Are Predictors of Distant Metastasis and Survival in Early-Stage Non-Small Cell Lung Cancer. Cancer Research. 64(16). 5564–5569. 168 indexed citations
14.
Mayer, Christian T., et al.. (2004). Release of cell fragments by invading melanoma cells. European Journal of Cell Biology. 83(11-12). 709–715. 35 indexed citations
15.
16.
Gebhardt, Frank, Kurt S. Zänker, & Burkhard Brandt. (1998). Differential Expression of Alternatively Spliced c-erbB-2 mRNA in Primary Tumors, Lymph Node Metastases, and Bone Marrow Micrometastases from Breast Cancer Patients. Biochemical and Biophysical Research Communications. 247(2). 319–323. 20 indexed citations
17.
Brandt, Burkhard, et al.. (1998). Isolation of blood-borne epithelium-derived c-erbB-2 oncoprotein-positive clustered cells from the peripheral blood of breast cancer patients. International Journal of Cancer. 76(6). 824–828. 69 indexed citations
18.
Bartholmes, Peter, et al.. (1997). Migration and gap junctional intercellular communication determine the metastatic phenotype of human tumor cell lines. Cancer Letters. 118(2). 181–187. 10 indexed citations
19.
Berdel, Wolfgang E., Eva Greiner, U. Fink, et al.. (1984). Cytotoxic Effects of Alkyl-Lysophospholipids in Human Brain Tumor Cells. Oncology. 41(2). 140–145. 26 indexed citations
20.
Zänker, Kurt S., et al.. (1980). Partial purification and characterization of phosphatidylcholine-binding proteins from rat lung lavage. Biochemical Medicine. 23(3). 239–256. 5 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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