Markus Möbs

1.4k total citations
42 papers, 802 citations indexed

About

Markus Möbs is a scholar working on Dermatology, Pathology and Forensic Medicine and Oncology. According to data from OpenAlex, Markus Möbs has authored 42 papers receiving a total of 802 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Dermatology, 19 papers in Pathology and Forensic Medicine and 14 papers in Oncology. Recurrent topics in Markus Möbs's work include Cutaneous lymphoproliferative disorders research (22 papers), Lymphoma Diagnosis and Treatment (15 papers) and T-cell and Retrovirus Studies (9 papers). Markus Möbs is often cited by papers focused on Cutaneous lymphoproliferative disorders research (22 papers), Lymphoma Diagnosis and Treatment (15 papers) and T-cell and Retrovirus Studies (9 papers). Markus Möbs collaborates with scholars based in Germany, United States and Austria. Markus Möbs's co-authors include Wolfram Sterry, Chalid Assaf, Marc Beyer, Daniel Humme, Jürgen Eberle, Frank Braun, Michael Hummel, Michael Plötz, Nadya Al‐Yacoub and Karsten Gülow and has published in prestigious journals such as Nature Communications, The Journal of Experimental Medicine and Journal of Clinical Oncology.

In The Last Decade

Markus Möbs

39 papers receiving 794 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Markus Möbs Germany 19 303 250 240 239 237 42 802
Kedar Inamdar United States 15 253 0.8× 276 1.1× 141 0.6× 67 0.3× 393 1.7× 39 772
Lorenza Pastorino Italy 21 525 1.7× 126 0.5× 116 0.5× 261 1.1× 734 3.1× 57 1.2k
Barbara MacGregor‐Cortelli United States 10 424 1.4× 500 2.0× 198 0.8× 149 0.6× 605 2.6× 12 1.1k
John R. Spaull United Kingdom 14 334 1.1× 96 0.4× 134 0.6× 125 0.5× 208 0.9× 17 878
Sébastien de Feraudy United States 13 174 0.6× 106 0.4× 76 0.3× 98 0.4× 277 1.2× 32 655
D C Louie United States 13 312 1.0× 369 1.5× 278 1.2× 34 0.1× 250 1.1× 16 852
Sakura Sakajiri Japan 14 272 0.9× 194 0.8× 110 0.5× 27 0.1× 358 1.5× 32 704
J.‐P. Magaud France 12 213 0.7× 348 1.4× 180 0.8× 71 0.3× 252 1.1× 24 845
Feifei Nan China 16 465 1.5× 399 1.6× 275 1.1× 40 0.2× 246 1.0× 38 794
A Rosolen Italy 19 263 0.9× 317 1.3× 252 1.1× 37 0.2× 366 1.5× 45 956

Countries citing papers authored by Markus Möbs

Since Specialization
Citations

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

Fields of papers citing papers by Markus Möbs

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Markus Möbs

This figure shows the co-authorship network connecting the top 25 collaborators of Markus Möbs. A scholar is included among the top collaborators of Markus Möbs 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 Markus Möbs. Markus Möbs 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.
Dragomir, Mihnea P., et al.. (2025). Spatial proteomics of ovarian cancer precursors delineates early disease changes and drug targets. Molecular Systems Biology. 22(1). 7–41. 2 indexed citations
2.
3.
Habringer, Stefan, Jana Ihlow, Max Schmidt, et al.. (2024). A diagnostic challenge of KIT p.V559D and BRAF p.G469A mutations in a paragastric mass. The Oncologist. 29(10). 908–912.
4.
Brand, Michiel van den, Markus Möbs, Leonie I. Kroeze, et al.. (2023). EuroClonality-NGS Recommendations for Evaluation of B-Cell Clonality Analysis by Next-Generation Sequencing. Journal of Molecular Diagnostics. 25(10). 729–739. 3 indexed citations
5.
Keppens, Cleo, Elke Boone, Paula Gameiro, et al.. (2021). Evaluation of a worldwide EQA scheme for complex clonality analysis of clinical lymphoproliferative cases demonstrates a learning effect. Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin. 479(2). 365–376. 2 indexed citations
6.
Brand, Michiel van den, Jos Rijntjes, Markus Möbs, et al.. (2021). Next-Generation Sequencing–Based Clonality Assessment of Ig Gene Rearrangements. Journal of Molecular Diagnostics. 23(9). 1105–1115. 23 indexed citations
7.
Arnold, Alexander, Christine Sers, Aysel Ahadova, et al.. (2020). The majority of β-catenin mutations in colorectal cancer is homozygous. BMC Cancer. 20(1). 1038–1038. 28 indexed citations
8.
Benten, Daniel, Gerrit Wolters‐Eisfeld, Susanne Burdak‐Rothkamm, et al.. (2018). Establishment of the First Well-differentiated Human Pancreatic Neuroendocrine Tumor Model. Molecular Cancer Research. 16(3). 496–507. 54 indexed citations
9.
10.
Nölting, Svenja, Helma Freitag, Katharina Detjen, et al.. (2017). The selective PI3Kα inhibitor BYL719 as a novel therapeutic option for neuroendocrine tumors: Results from multiple cell line models. PLoS ONE. 12(8). e0182852–e0182852. 28 indexed citations
11.
Briest, Franziska, Markus Möbs, Friederike Christen, et al.. (2017). Mechanisms of Targeting the MDM2-p53-FOXM1 Axis in Well-Differentiated Intestinal Neuroendocrine Tumors. Neuroendocrinology. 107(1). 1–23. 12 indexed citations
12.
Haider, Ahmed, Reinhard Ullmann, Michael Hummel, et al.. (2016). Inactivation of RUNX3/p46 Promotes Cutaneous T-Cell Lymphoma. Journal of Investigative Dermatology. 136(11). 2287–2296. 13 indexed citations
13.
Endris, Volker, Albrecht Stenzinger, Nicole Pfarr, et al.. (2016). NGS-based BRCA1/2 mutation testing of high-grade serous ovarian cancer tissue: results and conclusions of the first international round robin trial. Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin. 468(6). 697–705. 22 indexed citations
14.
Humme, Daniel, Ahmed Haider, Markus Möbs, et al.. (2015). Aurora Kinase A Is Upregulated in Cutaneous T-Cell Lymphoma and Represents a Potential Therapeutic Target. Journal of Investigative Dermatology. 135(9). 2292–2300. 18 indexed citations
15.
Ohmatsu, Hanako, Daniel Humme, Nicholas Gulati, et al.. (2014). IL32 Is Progressively Expressed in Mycosis Fungoides Independent of Helper T-cell 2 and Helper T-cell 9 Polarization. Cancer Immunology Research. 2(9). 890–900. 17 indexed citations
16.
Möbs, Markus, et al.. (2014). Analysis of the IL-31 pathway in Mycosis fungoides and Sézary syndrome. Archives of Dermatological Research. 307(6). 479–485. 22 indexed citations
17.
Zawada, M, Piotr Grabarczyk, Markus Möbs, et al.. (2013). Identification of Multiple Complex Rearrangements Associated with Deletions in the 6q23-27 Region in Sézary Syndrome. Journal of Investigative Dermatology. 134(2). 583–583. 1 indexed citations
18.
Zawada, M, Piotr Grabarczyk, Markus Möbs, et al.. (2013). Identification of Multiple Complex Rearrangements Associated with Deletions in the 6q23-27 Region in Sézary Syndrome. Journal of Investigative Dermatology. 133(11). 2617–2625. 8 indexed citations
19.
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
20.
Lukowsky, Ansgar, J. Marcus Muche, Markus Möbs, et al.. (2010). Evaluation of T-cell Clonality in Archival Skin Biopsy Samples of Cutaneous T-cell Lymphomas Using the Biomed-2 PCR Protocol. Diagnostic Molecular Pathology. 19(2). 70–77. 23 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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