Markus Feuerer

15.7k total citations · 5 hit papers
60 papers, 9.3k citations indexed

About

Markus Feuerer is a scholar working on Immunology, Oncology and Molecular Biology. According to data from OpenAlex, Markus Feuerer has authored 60 papers receiving a total of 9.3k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Immunology, 19 papers in Oncology and 7 papers in Molecular Biology. Recurrent topics in Markus Feuerer's work include Immune Cell Function and Interaction (40 papers), T-cell and B-cell Immunology (36 papers) and Immunotherapy and Immune Responses (31 papers). Markus Feuerer is often cited by papers focused on Immune Cell Function and Interaction (40 papers), T-cell and B-cell Immunology (36 papers) and Immunotherapy and Immune Responses (31 papers). Markus Feuerer collaborates with scholars based in Germany, United States and France. Markus Feuerer's co-authors include Diane Mathis, Christophe Benoıst, Jongsoon Lee, Daniela Cipolletta, Steven E. Shoelson, Jonathan A. Hill, Jamie Wong, David M. Richards, Allison B. Goldfine and Ali Nayer and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Markus Feuerer

60 papers receiving 9.1k citations

Hit Papers

Lean, but not obese, fat is enriched for a unique populat... 2004 2026 2011 2018 2009 2006 2012 2004 2021 500 1000 1.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Lean, but not obese, fat is enriched for a unique population of regulatory T cells that affect metabolic parameters
    2009 1.7k citations Markus Feuerer, Jamie Wong et al. Nature Medicine profile →
  2. FOXP3 Controls Regulatory T Cell Function through Cooperation with NFAT
    2006 937 citations Yongqing Wu, Vigo Heissmeyer et al. Cell profile →
  3. PPAR-γ is a major driver of the accumulation and phenotype of adipose tissue Treg cells
    2012 915 citations Markus Feuerer, Christophe Benoıst et al. profile →
  4. Developmental Stage, Phenotype, and Migration Distinguish Naive- and Effector/Memory-like CD4+ Regulatory T Cells
    2004 520 citations Jochen Huehn, Kerstin Siegmund et al. The Journal of Experimental Medicine profile →
  5. Inflammatory Response Mechanisms of the Dentine–Pulp Complex and the Periapical Tissues
    2021 258 citations Markus Feuerer et al. International Journal of Molecular Sciences profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Markus Feuerer Germany 38 6.6k 1.7k 1.6k 1.5k 1.1k 60 9.3k
Estelle Bettelli United States 24 9.0k 1.3× 1.6k 0.9× 1.8k 1.1× 857 0.6× 742 0.7× 36 11.8k
Angela M. Thornton United States 39 8.8k 1.3× 1.6k 1.0× 1.7k 1.1× 859 0.6× 505 0.5× 66 11.2k
Wendy M. Blumenschein United States 25 10.5k 1.6× 1.8k 1.1× 2.2k 1.4× 1.2k 0.8× 1.2k 1.1× 43 13.7k
Seon Hee Chang United States 35 8.4k 1.3× 1.9k 1.1× 1.9k 1.2× 802 0.5× 1.6k 1.5× 50 11.4k
Mark A. Exley United States 56 8.0k 1.2× 1.2k 0.7× 1.8k 1.1× 1.5k 1.0× 478 0.5× 124 10.3k
Brent S. McKenzie Australia 29 9.6k 1.4× 2.0k 1.2× 1.7k 1.0× 1.2k 0.8× 927 0.9× 45 12.5k
Naoto Ishii Japan 51 7.1k 1.1× 2.3k 1.4× 2.4k 1.5× 747 0.5× 694 0.7× 167 10.9k
William A. Kuziel United States 67 7.7k 1.2× 3.1k 1.9× 2.9k 1.8× 2.1k 1.3× 868 0.8× 125 13.9k
Ye Zheng United States 28 5.6k 0.8× 2.0k 1.2× 1.3k 0.8× 682 0.4× 596 0.6× 51 8.0k

Countries citing papers authored by Markus Feuerer

Since Specialization
Citations

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

Fields of papers citing papers by Markus Feuerer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Markus Feuerer

This figure shows the co-authorship network connecting the top 25 collaborators of Markus Feuerer. A scholar is included among the top collaborators of Markus Feuerer 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 Feuerer. Markus Feuerer 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.
Bittner, Sebastian, Thomas Hehlgans, & Markus Feuerer. (2023). Engineered Treg cells as putative therapeutics against inflammatory diseases and beyond. Trends in Immunology. 44(6). 468–483. 56 indexed citations
2.
Decking, Sonja-Maria, Christina Bruß, Sebastian Klobuch, et al.. (2022). LDHB Overexpression Can Partially Overcome T Cell Inhibition by Lactic Acid. International Journal of Molecular Sciences. 23(11). 5970–5970. 18 indexed citations
3.
Bittner, Sebastian, Lisa Schmidleithner, Asmita Pant, et al.. (2022). Biosensors for inflammation as a strategy to engineer regulatory T cells for cell therapy. Proceedings of the National Academy of Sciences. 119(40). e2208436119–e2208436119. 23 indexed citations
4.
Eisel, David, Mathias Vormehr, Karin Müller‐Decker, et al.. (2019). A transplantable tumor model allowing investigation of NY-BR-1-specific T cell responses in HLA-DRB1*0401 transgenic mice. BMC Cancer. 19(1). 914–914. 1 indexed citations
5.
Delacher, Michael, Charles D. Imbusch, Dieter Weichenhan, et al.. (2017). Genome-wide DNA-methylation landscape defines specialization of regulatory T cells in tissues. Nature Immunology. 18(10). 1160–1172. 196 indexed citations
6.
Hanna, Bola S., Murat Iskar, Norman Mack, et al.. (2017). IL-10 Receptor Deficiency Aggravates Exhaustion of CD8+ T-Cells and Impedes Their Control of Chronic Lymphocytic Leukemia. Blood. 130. 385–385. 2 indexed citations
7.
Medříková, Daša, Tjeerd Sijmonsma, David M. Richards, et al.. (2015). Brown Adipose Tissue Harbors a Distinct Sub-Population of Regulatory T Cells. PLoS ONE. 10(2). e0118534–e0118534. 63 indexed citations
8.
Richards, David M., Michael Delacher, Yael Goldfarb, et al.. (2015). Treg Cell Differentiation: From Thymus to Peripheral Tissue. Progress in molecular biology and translational science. 136. 175–205. 45 indexed citations
9.
Richards, David M., et al.. (2015). Premature Expression of Foxp3 in Double-Negative Thymocytes. PLoS ONE. 10(5). e0127038–e0127038. 3 indexed citations
10.
Feuerer, Markus, Jonathan A. Hill, Karsten Kretschmer, et al.. (2010). Genomic definition of multiple ex vivo regulatory T cell subphenotypes. Proceedings of the National Academy of Sciences. 107(13). 5919–5924. 173 indexed citations
11.
Nishio, Junko, Markus Feuerer, Jamie Wong, Diane Mathis, & Christophe Benoıst. (2010). Anti-CD3 therapy permits regulatory T cells to surmount T cell receptor–specified peripheral niche constraints. The Journal of Experimental Medicine. 207(9). 1879–1889. 56 indexed citations
12.
Sundrud, Mark S., Sergei B. Koralov, Markus Feuerer, et al.. (2009). Halofuginone Inhibits T H 17 Cell Differentiation by Activating the Amino Acid Starvation Response. Science. 324(5932). 1334–1338. 323 indexed citations
13.
D’Alise, Anna Morena, Vincent C. Auyeung, Markus Feuerer, et al.. (2008). The defect in T-cell regulation in NOD mice is an effect on the T-cell effectors. Proceedings of the National Academy of Sciences. 105(50). 19857–19862. 164 indexed citations
14.
Feuerer, Markus, Wenyu Jiang, Phillip D. Holler, et al.. (2007). Enhanced thymic selection of FoxP3 + regulatory T cells in the NOD mouse model of autoimmune diabetes. Proceedings of the National Academy of Sciences. 104(46). 18181–18186. 63 indexed citations
15.
Feuerer, Markus, Katharina Eulenburg, Christoph Loddenkemper, Alf Hamann, & Jochen Huehn. (2006). Self-Limitation of Th1-Mediated Inflammation by IFN-γ. The Journal of Immunology. 176(5). 2857–2863. 72 indexed citations
16.
Wu, Yongqing, Vigo Heissmeyer, Markus Feuerer, et al.. (2006). FOXP3 Controls Regulatory T Cell Function through Cooperation with NFAT. Cell. 126(2). 375–387. 937 indexed citations breakdown →
17.
Siegmund, Kerstin, Markus Feuerer, Christiane Siewert, et al.. (2005). Migration matters: regulatory T-cell compartmentalization determines suppressive activity in vivo. Blood. 106(9). 3097–3104. 213 indexed citations
18.
Beckhove, Philipp, Markus Feuerer, Florian Schuetz, et al.. (2004). Specifically activated memory T cell subsets from cancer patients recognize and reject xenotransplanted autologous tumors. Journal of Clinical Investigation. 114(1). 67–76. 103 indexed citations
19.
Feuerer, Markus, Philipp Beckhove, Lianhua Bai, et al.. (2001). Therapy of human tumors in NOD/SCID mice with patient-derived reactivated memory T cells from bone marrow. Nature Medicine. 7(4). 452–458. 229 indexed citations
20.
Feuerer, Markus, Marian Rocha, Lianhua Bai, et al.. (2001). Enrichment of memory T cells and other profound immunological changes in the bone marrow from untreated breast cancer patients. International Journal of Cancer. 92(1). 96–105. 134 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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