Stefan Größ
- Molecular Biology top 2%
- Cancer Research top 0.5%
- Genetics top 0.2%
- Hematology top 1%
- Oncology top 5%
- Co-authors
- Lenny DangValeria R. FantinShengfang JinShinsan M. SuEdward M. DriggersHyun Gyung JangMark BittingerKevin M. Marks
- Topics
- Cancer, Hypoxia, and Metabolism (12 papers)Glioma Diagnosis and Treatment (6 papers)Epigenetics and DNA Methylation (5 papers)
- Cited by
- Cancer ResearchGeneticsHematology
- Partner nations
- United StatesGermanyChina
In The Last Decade
Stefan Größ
24 papers receiving 5.4k citations
Hit Papers
Peers
Comparison fields: 5 of 121
- Molecular Biology 3.5k
- Cancer Research 2.8k
- Genetics 1.8k
- Hematology 691
- Oncology 570
Countries citing papers authored by Stefan Größ
This map shows the geographic impact of Stefan Größ'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 Stefan Größ with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefan Größ more than expected).
Fields of papers citing papers by Stefan Größ
This network shows the impact of papers produced by Stefan Größ. 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 Stefan Größ. The network helps show where Stefan Größ may publish in the future.
Co-authorship network of co-authors of Stefan Größ
This figure shows the co-authorship network connecting the top 25 collaborators of Stefan Größ. A scholar is included among the top collaborators of Stefan Größ 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 Stefan Größ. Stefan Größ is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 16 | |
| 3 | 17 | |
| 4 | 99 | |
| 5 | 12 | |
| 6 | Der Wirtschaftsprüfer 2.0 im digitalen Öko-System | 1 |
| 7 | 280 | |
| 8 | 72 | |
| 9 | 39 | |
| 10 | 2 | |
| 11 | 18 | |
| 12 | ML309: A potent inhibitor of R132H mutant IDH1 capable of reducing 2-hydroxyglutarate production in U87 MG glioblastoma cells | 16 |
| 13 | 160 | |
| 14 | Transformation by the (R)-enantiomer of 2-hydroxyglutarate linked to EGLN activationbreakdown → | 566 |
| 15 | 123 | |
| 16 | Cancer-associated metabolite 2-hydroxyglutarate accumulates in acute myelogenous leukemia with isocitrate dehydrogenase 1 and 2 mutationsbreakdown → | 558 |
| 17 | 4 | |
| 18 | Cancer-associated IDH1 mutations produce 2-hydroxyglutaratebreakdown → | 3067 |
| 19 | 1 | |
| 20 | 21 |
About Stefan Größ
Stefan Größ is a scholar working on Cancer Research, Genetics and Biochemistry, having authored 27 papers that have together received 5.5k indexed citations. Recurring topics across this work include Cancer, Hypoxia, and Metabolism (12 papers), Glioma Diagnosis and Treatment (6 papers) and Epigenetics and DNA Methylation (5 papers). The work is most often cited by research in Cancer Research (2.8k citations), Genetics (1.8k citations) and Hematology (691 citations). Stefan Größ has collaborated with scholars based in United States, Germany and China. Frequent co-authors include Lenny Dang, Valeria R. Fantin, Shengfang Jin, Shinsan M. Su, Edward M. Driggers, Hyun Gyung Jang, Mark Bittinger, Kevin M. Marks, Katharine Yen and Marie C. Keenan. Their work appears in journals such as Nature, Journal of Biological Chemistry and Nature Communications.
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.