Stephan Mathas

5.7k total citations
55 papers, 3.2k citations indexed

About

Stephan Mathas is a scholar working on Pathology and Forensic Medicine, Oncology and Immunology. According to data from OpenAlex, Stephan Mathas has authored 55 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Pathology and Forensic Medicine, 24 papers in Oncology and 20 papers in Immunology. Recurrent topics in Stephan Mathas's work include Lymphoma Diagnosis and Treatment (30 papers), NF-κB Signaling Pathways (11 papers) and Immune Cell Function and Interaction (9 papers). Stephan Mathas is often cited by papers focused on Lymphoma Diagnosis and Treatment (30 papers), NF-κB Signaling Pathways (11 papers) and Immune Cell Function and Interaction (9 papers). Stephan Mathas collaborates with scholars based in Germany, United States and Norway. Stephan Mathas's co-authors include Bernd Dörken, Franziska Jundt, Ioannis Anagnostopoulos, Harald Stein, Claus Scheidereit, Kurt Bommert, Daniel Krappmann, Martin Janz, M. Hinz and Reinhold Förster and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and The Journal of Experimental Medicine.

In The Last Decade

Stephan Mathas

53 papers receiving 3.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Stephan Mathas Germany 27 1.4k 1.3k 1.2k 1.0k 695 55 3.2k
Javeed Iqbal United States 28 961 0.7× 1.4k 1.1× 970 0.8× 868 0.8× 506 0.7× 115 2.8k
Franziska Jundt Germany 25 1.2k 0.8× 762 0.6× 856 0.7× 778 0.7× 455 0.7× 45 2.6k
Antonella Aiello Italy 26 1.4k 1.0× 1.0k 0.8× 917 0.8× 662 0.6× 267 0.4× 61 3.1k
M Stetler-Stevenson United States 22 680 0.5× 677 0.5× 869 0.7× 735 0.7× 330 0.5× 44 2.3k
Marco Herling Germany 29 729 0.5× 1.2k 1.0× 1.1k 0.9× 1.1k 1.1× 226 0.3× 118 3.0k
Kunihiko Takeyama United States 16 979 0.7× 936 0.7× 1.4k 1.2× 928 0.9× 192 0.3× 41 2.7k
Norihiko Kawamata Japan 38 2.2k 1.6× 745 0.6× 1.4k 1.1× 467 0.4× 588 0.8× 96 4.0k
Sivasundaram Karnan Japan 24 1.3k 1.0× 659 0.5× 548 0.5× 398 0.4× 795 1.1× 72 2.3k
Masaaki Higashihara Japan 25 675 0.5× 618 0.5× 477 0.4× 542 0.5× 269 0.4× 127 2.1k
Chris Saris United States 19 1.5k 1.1× 632 0.5× 926 0.8× 881 0.8× 224 0.3× 25 3.3k

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-authorship network of co-authors of Stephan Mathas

This figure shows the co-authorship network connecting the top 25 collaborators of Stephan Mathas. A scholar is included among the top collaborators of Stephan Mathas 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 Stephan Mathas. Stephan Mathas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Blanc, Eric, Hanna Napieczyńska, Barbara Walter, et al.. (2023). Mouse models of human multiple myeloma subgroups. Proceedings of the National Academy of Sciences. 120(10). e2219439120–e2219439120. 5 indexed citations
2.
3.
Schildgen, Oliver, Dirk Schürmann, Martin Janz, et al.. (2021). High-dose glucocorticoid treatment of near-fatal bocavirus lung infection results in rapid recovery. ERJ Open Research. 7(2). 60–2021. 1 indexed citations
4.
Cauchy, Pierre, Salam A. Assi, Sylvia Hartmann, et al.. (2018). Global long terminal repeat activation participates in establishing the unique gene expression programme of classical Hodgkin lymphoma. Leukemia. 33(6). 1463–1474. 15 indexed citations
5.
Richter, Julia, Maciej Giefing, Sylvia Hartmann, et al.. (2016). Inactivation of the putative ubiquitin-E3 ligase PDLIM2 in classical Hodgkin and anaplastic large cell lymphoma. Leukemia. 31(3). 602–613. 13 indexed citations
6.
Mathas, Stephan, Sylvia Hartmann, & Ralf Küppers. (2016). Hodgkin lymphoma: Pathology and biology. Seminars in Hematology. 53(3). 139–147. 88 indexed citations
7.
Kaergel, Eva, Matthias Heinig, Jean−Fred Fontaine, et al.. (2016). A roadmap of constitutive NF-κB activity in Hodgkin lymphoma: Dominant roles of p50 and p52 revealed by genome-wide analyses. Genome Medicine. 8(1). 28–28. 47 indexed citations
8.
Schwefel, David, Stephen F. Marino, Björn Lamprecht, et al.. (2013). Structural Insights into the Mechanism of GTPase Activation in the GIMAP Family. Structure. 21(4). 550–559. 36 indexed citations
9.
Lamprecht, Björn, Stephan Kreher, Markus Möbs, et al.. (2012). The tumour suppressor p53 is frequently nonfunctional in Sézary syndrome. British Journal of Dermatology. 167(2). 240–246. 22 indexed citations
10.
11.
Lamprecht, Björn, Constanze Bonifer, & Stephan Mathas. (2010). Repeat element-driven activation of proto-oncogenes in human malignancies. Cell Cycle. 9(21). 4276–4281. 10 indexed citations
12.
Ratei, Richard, Michael Hummel, Ioannis Anagnostopoulos, et al.. (2010). Common clonal origin of an acute B-lymphoblastic leukemia and a Langerhans' cell sarcoma: evidence for hematopoietic plasticity. Haematologica. 95(9). 1461–1466. 39 indexed citations
13.
Köchert, Karl, Stephan Kreher, Jon C. Aster, et al.. (2010). High-level expression of Mastermind-like 2 contributes to aberrant activation of the NOTCH signaling pathway in human lymphomas. Oncogene. 30(15). 1831–1840. 38 indexed citations
14.
Mathas, Stephan, Bernd Dörken, & Martin Janz. (2009). Die molekulare Pathogenese des klassischen Hodgkin-Lymphoms. DMW - Deutsche Medizinische Wochenschrift. 134(39). 1944–1948. 3 indexed citations
15.
Jundt, Franziska, Sun‐Ho Kwon, Rolf Schwarzer, et al.. (2008). Aberrant expression of Notch1 interferes with the B-lymphoid phenotype of neoplastic B cells in classical Hodgkin lymphoma. Leukemia. 22(8). 1587–1594. 59 indexed citations
16.
Subklewe, Marion, et al.. (2007). Dendritic Cell Maturation Stage Determines Susceptibility to the Proteasome Inhibitor Bortezomib. Human Immunology. 68(3). 147–155. 39 indexed citations
17.
Mathas, Stephan. (2007). The Pathogenesis of Classical Hodgkin's Lymphoma: A Model for B-Cell Plasticity. Hematology/Oncology Clinics of North America. 21(5). 787–804. 8 indexed citations
18.
Mathas, Stephan, Martin Janz, Michael Hummel, et al.. (2005). Intrinsic inhibition of transcription factor E2A by HLH proteins ABF-1 and Id2 mediates reprogramming of neoplastic B cells in Hodgkin lymphoma. Nature Immunology. 7(2). 207–215. 128 indexed citations
19.
Mathas, Stephan. (2002). Aberrantly expressed c-Jun and JunB are a hallmark of Hodgkin lymphoma cells, stimulate proliferation and synergize with NF-kappaB. The EMBO Journal. 21(15). 4104–4113. 293 indexed citations
20.
Mathas, Stephan, Anke Rickers, Kurt Bommert, Bernd Dörken, & Markus Y. Mapara. (2000). Anti-CD20- and B-cell receptor-mediated apoptosis: evidence for shared intracellular signaling pathways.. MDC Repository (Max-Delbrueck-Center for Molecular Medicine). 60(24). 7170–6. 127 indexed citations

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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