Stefan Gesk
Impact in
- Pathology and Forensic Medicine top 0.2%
- Lymphoma Diagnosis and Treatment
- Cancer Mechanisms and Therapy
- Genetics top 0.5%
- Chronic Lymphocytic Leukemia Research
Papers in
-
- Lymphoma Diagnosis and Treatment 44
- Genetics 28
- Chronic Lymphocytic Leukemia Research 26
- Genomic variations and chromosomal abnormalities 7
- Co-authors
- Reiner Siebert (53 shared papers)José I. Martín‐Subero (27 shared papers)Lana Harder (29 shared papers)Reiner Siebert (21 shared papers)Brigitte Schlegelberger (16 shared papers)Martin J.S. Dyer (14 shared papers)Inga Vater (9 shared papers)Wolfgang Hiddemann (14 shared papers)
- Journals
- Blood (15 papers)British Journal of Haematology (8 papers)Genes Chromosomes and Cancer (6 papers)Haematologica (6 papers)Leukemia (6 papers)
- Partner nations
- GermanyUnited KingdomSpain
In The Last Decade
Stefan Gesk
80 papers receiving 4.3k citations
Peers
Comparison fields: 5 of 92
- Pathology and Forensic Medicine 2.3k
- Genetics 1.1k
- Oncology 1.2k
- Cancer Research 592
- Immunology 803
Countries citing papers authored by Stefan Gesk
This map shows the geographic impact of Stefan Gesk'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 Gesk with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefan Gesk more than expected).
Fields of papers citing papers by Stefan Gesk
This network shows the impact of papers produced by Stefan Gesk. 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 Gesk. The network helps show where Stefan Gesk may publish in the future.
Co-authors
The 25 scholars most cited alongside Stefan Gesk, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 81 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 346 | |
| 2 | 2001 | 243 | |
| 3 | 2010 | 223 | |
| 4 | 2006 | 208 | |
| 5 | 2002 | 173 | |
| 6 | 2011 | 168 | |
| 7 | 2002 | 166 | |
| 8 | 2010 | 152 | |
| 9 | 2004 | 125 | |
| 10 | 2005 | 121 | |
| 11 | 2000 | 116 | |
| 12 | 2001 | 88 | |
| 13 | 2003 | 85 | |
| 14 | 2009 | 76 | |
| 15 | 2008 | 76 | |
| 16 | 2012 | 75 | |
| 17 | 2004 | 71 | |
| 18 | 2009 | 71 | |
| 19 | 2002 | 70 | |
| 20 | 2009 | 68 |
About Stefan Gesk
Stefan Gesk is a scholar working on Pathology and Forensic Medicine, Genetics, Molecular Biology, Oncology and Immunology, having authored 81 papers that have together received 4.3k indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (44 papers), Chronic Lymphocytic Leukemia Research (26 papers), Viral-associated cancers and disorders (15 papers), Genomic variations and chromosomal abnormalities (7 papers), NF-κB Signaling Pathways (7 papers), Ubiquitin and proteasome pathways (5 papers), T-cell and Retrovirus Studies (5 papers) and Chronic Myeloid Leukemia Treatments (5 papers). The work is most often cited by research in Pathology and Forensic Medicine (2.3k citations), Genetics (1.1k citations), Oncology (1.2k citations), Cancer Research (592 citations) and Immunology (803 citations). Stefan Gesk has collaborated with scholars based in Germany, United Kingdom and Spain. Frequent co-authors include Reiner Siebert, José I. Martín‐Subero, Lana Harder, Reiner Siebert, Brigitte Schlegelberger, Martin J.S. Dyer, Inga Vater, Wolfgang Hiddemann, Ralf Küppers and W. Grote. Their work appears in journals such as Blood, British Journal of Haematology, Genes Chromosomes and Cancer, Haematologica and Leukemia.
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.