Stephan Mathas

83 papers receiving 4.7k citations

Stephan Mathas's Hit Papers

Assessing the efficacy and tolerability of PET-guided BrECADD versus eBEACOPP in advanced-stage, classical Hodgkin lymphoma (HD21): a randomised, multicentre, parallel, open-label, phase 3 trial 2024 · 68 citations
680+1Years since publication204060

Peers

Stephan Mathas
Comparison fields: 5 of 89
  • Pathology and Forensic Medicine 2k
  • Cancer Research 580
  • Oncology 616
  • Hematology 338
  • Immunology 349
Replace Martin Janz with:
Martin Janz Germany
Patricia A. Gorman United Kingdom
Wei Xu China
Karl Köchert Germany
Kimberley M. Howarth United Kingdom
Colette Adida France
Jing Yin United States
Rama Modali United States
Norihiko Kawamata Japan
Guilin Tang United States
Stephan Mathas relative to Martin Janz Germany Martin Janz's profile →
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Countries citing papers authored by Stephan Mathas

Since Specialization
Citations

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

Fields of papers citing papers by Stephan Mathas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Stephan Mathas, 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 Stephan Mathas Line = papers co-authored together Stephan Mathas links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 84 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002325
2 2002319
3 2010302
4 2001232
5 1999228
6 2002223
7 2004181
8 2004168
9 2005151
10 2003143
11
Anti-CD20- and B-cell receptor-mediated apoptosis: evidence for shared intracellular signaling pathways.
2000134
12 2014134
13 2020128
14 2005112
15 2016107
16 2005106
17 200892
18 201792
19 201484
20 200283

About Stephan Mathas

Stephan Mathas is a scholar working on Pathology and Forensic Medicine, Cancer Research, Hematology, Molecular Biology and Immunology, having authored 84 papers that have together received 4.8k indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (52 papers), Genomics and Chromatin Dynamics (11 papers), NF-κB Signaling Pathways (7 papers), Multiple Myeloma Research and Treatments (6 papers), Immunotherapy and Immune Responses (4 papers), Cutaneous lymphoproliferative disorders research (3 papers), Developmental Biology and Gene Regulation (3 papers) and Viral-associated cancers and disorders (2 papers). The work is most often cited by research in Pathology and Forensic Medicine (2k citations), Cancer Research (580 citations), Oncology (616 citations), Hematology (338 citations) and Immunology (349 citations). Stephan Mathas has collaborated with scholars based in Germany, United States and Austria. Frequent co-authors include Bernd Dörken, Franziska Jundt, Ioannis Anagnostopoulos, Harald Stein, Claus Scheidereit, Daniel Krappmann, Martin Janz, Kurt Bommert, Andreas Lietz and Michael Hummel. Their work appears in journals such as Blood, Leukemia, Nature Communications, Haematologica and The Journal of Experimental Medicine.

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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