Nina Kramer
Impact in
- Oncology top 5%
- Cancer Cells and Metastasis
- Cancer Research top 5%
- Cancer, Hypoxia, and Metabolism
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
Papers in
-
- Mathematical Biology Tumor Growth 3
- Oncology 13
- Cancer Cells and Metastasis 11
- Cytokine Signaling Pathways and Interactions 3
- Co-authors
- Helmut DolznigMarkus HengstschlägerChristine UngerAngelika WalzlGeorg KrupitzaMargit RosnerDaniela UnterleuthnerMartin Scherzer
- Journals
- SLAS DISCOVERY (2 papers)Scientific Reports (2 papers)International Journal of Molecular Sciences (2 papers)Cancers (2 papers)Oncogene (2 papers)
- Partner nations
- AustriaGermanyUnited States
In The Last Decade
Nina Kramer
24 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 121
- Oncology 855
- Cancer Research 384
- Cell Biology 302
- Biomedical Engineering 643
- Biophysics 73
Countries citing papers authored by Nina Kramer
This map shows the geographic impact of Nina Kramer'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 Nina Kramer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nina Kramer more than expected).
Fields of papers citing papers by Nina Kramer
This network shows the impact of papers produced by Nina Kramer. 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 Nina Kramer. The network helps show where Nina Kramer may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Nina Kramer, 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 | 2024 | 4 | |
| 2 | 2023 | 5 | |
| 3 | 2020 | 31 | |
| 4 | 2019 | 5 | |
| 5 | 2019 | 220 | |
| 6 | 2019 | 2 | |
| 7 | 2018 | 67 | |
| 8 | 2017 | 105 | |
| 9 | 2017 | 61 | |
| 10 | 2017 | 13 | |
| 11 | 2016 | 6 | |
| 12 | 2016 | 30 | |
| 13 | 2016 | 317 | |
| 14 | 2015 | 37 | |
| 15 | 2015 | 52 | |
| 16 | 2014 | 116 | |
| 17 | In vitro cell migration and invasion assays Hit paper breakdown → | 2012 | 901 |
| 18 | 2011 | 16 | |
| 19 | Effect of Helicobacter pylori on dbc-AMP stimulated acid secretion by human parietal cells. | 1994 | 5 |
| 20 | 1961 | 44 |
About Nina Kramer
Nina Kramer is a scholar working on Modeling and Simulation, Oncology, Cell Biology, Biomedical Engineering and Gastroenterology, having authored 24 papers that have together received 2.2k indexed citations. Recurring topics across this work include Cancer Cells and Metastasis (11 papers), 3D Printing in Biomedical Research (8 papers), Mathematical Biology Tumor Growth (3 papers), Helicobacter pylori-related gastroenterology studies (3 papers), Cellular Mechanics and Interactions (3 papers), Wnt/β-catenin signaling in development and cancer (3 papers), Veterinary Oncology Research (3 papers) and Cytokine Signaling Pathways and Interactions (3 papers). The work is most often cited by research in Oncology (855 citations), Cancer Research (384 citations), Cell Biology (302 citations), Biomedical Engineering (643 citations) and Biophysics (73 citations). Nina Kramer has collaborated with scholars based in Austria, Germany and United States. Frequent co-authors include Helmut Dolznig, Markus Hengstschläger, Christine Unger, Angelika Walzl, Georg Krupitza, Margit Rosner, Daniela Unterleuthner, Martin Scherzer, Stefanie Walter and Mira Stadler. Their work appears in journals such as SLAS DISCOVERY, Scientific Reports, International Journal of Molecular Sciences, Cancers and Oncogene.
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.