Peter Kaskel

41 papers receiving 1.5k citations

Peers

Peter Kaskel
Comparison fields: 5 of 103
  • Genetics 321
  • Dermatology 226
  • Oncology 381
  • Epidemiology 355
  • Cancer Research 158
Replace Ágota Szepesi with:
Ágota Szepesi Hungary
Georg Weinlich Austria
Paul Drillenburg Netherlands
Luís A. Corchete Spain
Kunihiko Takeyama United States
Andrea Staratschek‐Jox Germany
Michael I. Jesson United States
Walter King United States
Ruby Phelps United States
Nicolaus Friedrichs Germany
Peter Kaskel relative to Ágota Szepesi Hungary Ágota Szepesi's profile →
Citations per field
00.5×4.4×
Ágota Szepesi · 1×
Citations per year

Countries citing papers authored by Peter Kaskel

Since Specialization
Citations

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

Fields of papers citing papers by Peter Kaskel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter Kaskel. 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 Peter Kaskel. The network helps show where Peter Kaskel may publish in the future.

Co-authors

The 25 scholars most cited alongside Peter Kaskel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Peter Kaskel Line = papers co-authored together Peter Kaskel links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1995314
2
Allelic losses on chromosomes 14, 10, and 1 in atypical and malignant meningiomas: a genetic model of meningioma progression.
1995193
3 2000123
4 2001105
5 200194
6 200479
7 199977
8 200168
9
S100 beta is a more reliable tumor marker in peripheral blood for patients with newly occurred melanoma metastases compared with MIA, albumin and lactate-dehydrogenase.
200164
10 200053
11 199946
12 200045
13 200233
14 201433
15 200032
16 201020
17 200220
18 200719
19 201415
20 201714

About Peter Kaskel

Peter Kaskel is a scholar working on Oncology, Molecular Biology, Infectious Diseases, Pulmonary and Respiratory Medicine and Epidemiology, having authored 43 papers that have together received 1.6k indexed citations. Recurring topics across this work include Cutaneous Melanoma Detection and Management (6 papers), Antifungal resistance and susceptibility (6 papers), Cancer Genomics and Diagnostics (3 papers), Skin Protection and Aging (3 papers), Melanoma and MAPK Pathways (3 papers), Psoriasis: Treatment and Pathogenesis (3 papers), S100 Proteins and Annexins (2 papers) and Fungal Infections and Studies (2 papers). The work is most often cited by research in Genetics (321 citations), Dermatology (226 citations), Oncology (381 citations), Epidemiology (355 citations) and Cancer Research (158 citations). Peter Kaskel has collaborated with scholars based in Germany, United States and Spain. Frequent co-authors include Gertraud Krähn, Ulrike Leiter, R. U. Peter, Andreas von Deimling, Silvia Sander, Jochen Utikal, Sebastian Brandner, Jens Koopmann, David N. Louis and Johannes Schramm. Their work appears in journals such as British Journal of Dermatology, Journal of the American Academy of Dermatology, Journal of the European Academy of Dermatology and Venereology, BMC Health Services Research and The Oncologist.

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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