Udo Baron

8.5k total citations · 5 hit papers
44 papers, 6.8k citations indexed

About

Udo Baron is a scholar working on Immunology, Molecular Biology and Genetics. According to data from OpenAlex, Udo Baron has authored 44 papers receiving a total of 6.8k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Immunology, 16 papers in Molecular Biology and 13 papers in Genetics. Recurrent topics in Udo Baron's work include Immune Cell Function and Interaction (23 papers), T-cell and B-cell Immunology (21 papers) and CRISPR and Genetic Engineering (8 papers). Udo Baron is often cited by papers focused on Immune Cell Function and Interaction (23 papers), T-cell and B-cell Immunology (21 papers) and CRISPR and Genetic Engineering (8 papers). Udo Baron collaborates with scholars based in Germany, United States and Italy. Udo Baron's co-authors include Klaus Rajewsky, Frieder Schwenk, Sven Olek, Hermann Bujard, Jochen Huehn, Stefan Floess, Alf Hamann, Julia K. Polansky, Wolfgang Hillen and Mazahir T. Hasan and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Blood.

In The Last Decade

Udo Baron

42 papers receiving 6.7k citations

Hit Papers

Acre-transgenic mouse strain for the ubiquitous deletion ... 1995 2026 2005 2015 1995 2007 2000 2008 2007 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Udo Baron Germany 27 3.4k 2.7k 1.5k 931 473 44 6.8k
Christopher H. Clegg United States 36 2.1k 0.6× 3.0k 1.1× 885 0.6× 959 1.0× 459 1.0× 63 5.8k
Masafumi Onodera Japan 38 1.8k 0.5× 2.0k 0.7× 787 0.5× 803 0.9× 345 0.7× 123 5.2k
Dimitris Kioussis United Kingdom 52 5.1k 1.5× 3.9k 1.4× 1.4k 0.9× 1.2k 1.3× 369 0.8× 111 9.5k
Frank Köntgen Australia 25 5.0k 1.5× 3.7k 1.4× 910 0.6× 1.4k 1.5× 552 1.2× 28 9.2k
Camilynn I. Brannan United States 34 3.3k 1.0× 6.1k 2.2× 2.6k 1.7× 935 1.0× 691 1.5× 46 10.2k
Eisuke Mekada Japan 48 2.4k 0.7× 4.2k 1.5× 624 0.4× 2.0k 2.1× 268 0.6× 130 8.4k
Yousuke Takahama Japan 55 6.4k 1.9× 3.9k 1.4× 980 0.7× 2.2k 2.4× 486 1.0× 188 10.8k
Hubert Schorle Germany 45 2.7k 0.8× 4.6k 1.7× 1.7k 1.2× 1.0k 1.1× 498 1.1× 135 8.8k
Yanick J. Crow United Kingdom 54 5.7k 1.7× 5.9k 2.2× 1.6k 1.1× 1.0k 1.1× 1.2k 2.5× 177 10.9k
Ken‐ichi Yamamura Japan 27 1.3k 0.4× 4.3k 1.6× 1.9k 1.3× 632 0.7× 975 2.1× 89 7.2k

Countries citing papers authored by Udo Baron

Since Specialization
Citations

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

Fields of papers citing papers by Udo Baron

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Udo Baron

This figure shows the co-authorship network connecting the top 25 collaborators of Udo Baron. A scholar is included among the top collaborators of Udo Baron 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 Udo Baron. Udo Baron 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.
Schlundt, Claudia, Simon Reinke, Sven Geißler, et al.. (2019). Individual Effector/Regulator T Cell Ratios Impact Bone Regeneration. Frontiers in Immunology. 10. 1954–1954. 71 indexed citations
2.
Stervbo, Ulrik, Dominika Pohlmann, Udo Baron, et al.. (2017). Age dependent differences in the kinetics of γδ T cells after influenza vaccination. PLoS ONE. 12(7). e0181161–e0181161. 17 indexed citations
4.
Stervbo, Ulrik, Udo Baron, Cecilia Bozzetti, et al.. (2015). Effects of aging on human leukocytes (part I): immunophenotyping of innate immune cells. AGE. 37(5). 92–92. 39 indexed citations
5.
Stervbo, Ulrik, Cecilia Bozzetti, Udo Baron, et al.. (2015). Effects of aging on human leukocytes (part II): immunophenotyping of adaptive immune B and T cell subsets. AGE. 37(5). 535–536. 22 indexed citations
6.
Thomas, Alissa A., James L. Fisher, Gilbert J. Rahme, et al.. (2015). Regulatory T cells are not a strong predictor of survival for patients with glioblastoma. Neuro-Oncology. 17(6). 801–809. 46 indexed citations
7.
Sebode, Marcial, Moritz Peiseler, Dorothee Schwinge, et al.. (2014). Reduced FOXP3+ regulatory T cells in patients with primary sclerosing cholangitis are associated with IL2RA gene polymorphisms. Journal of Hepatology. 60(5). 1010–1016. 84 indexed citations
8.
Ukena, Sya N., Sarvari Velaga, Philipp Ivanyi, et al.. (2011). Isolation strategies of regulatory T cells for clinical trials: Phenotype, function, stability, and expansion capacity. Experimental Hematology. 39(12). 1152–1160. 43 indexed citations
9.
Sehouli, Jalid, Christoph Loddenkemper, Tatjana I. Cornu, et al.. (2011). Epigenetic quantification of tumor-infiltrating T-lymphocytes. Epigenetics. 6(2). 236–246. 64 indexed citations
10.
Putnam, Amy, Michael R. F. Lee, Jonathan H. Esensten, et al.. (2011). Plasticity of Human Regulatory T Cells in Healthy Subjects and Patients with Type 1 Diabetes. The Journal of Immunology. 186(7). 3918–3926. 345 indexed citations
11.
Loddenkemper, Christoph, Jonas Stanke, Dirk Nagorsen, et al.. (2009). Regulatory (FOXP3+) T cells as target for immune therapy of cervical intraepithelial neoplasia and cervical cancer. Cancer Science. 100(6). 1112–1117. 56 indexed citations
12.
Polansky, Julia K., Karsten Kretschmer, Jennifer Freyer, et al.. (2008). DNA methylation controls Foxp3 gene expression. European Journal of Immunology. 38(6). 1654–1663. 615 indexed citations breakdown →
13.
Zhu, Peixin, M. Isabel Aller, Udo Baron, et al.. (2007). Silencing and Un-silencing of Tetracycline-Controlled Genes in Neurons. PLoS ONE. 2(6). e533–e533. 106 indexed citations
14.
Baron, Udo, Ivana Türbachova, Florian Eckhardt, et al.. (2006). DNA Methylation Analysis as a Tool for Cell Typing. Epigenetics. 1(1). 56–61. 50 indexed citations
15.
Baron, Udo. (2003). Kalter Krieg und heisser Frieden : der Einfluss der SED und ihrer westdeutschen Verbundeten auf die Partei "Die Grunen". Lit eBooks. 2 indexed citations
16.
Baron, Udo & Hermann Bujard. (2000). Tet repressor-based system for regulated gene expression in eukaryotic cells: Principles and advances. Methods in enzymology on CD-ROM/Methods in enzymology. 327. 401–421. 272 indexed citations
17.
Freundlieb, Sabine, et al.. (1997). Use of tetracycline-controlled gene expression systems to study mammalian cell cycle. Methods in enzymology on CD-ROM/Methods in enzymology. 283. 159–173. 49 indexed citations
18.
Baron, Udo, et al.. (1995). Co-regulation of two gene activities by tetracycline via a bidirectional promoter. Nucleic Acids Research. 23(17). 3605–3606. 274 indexed citations
19.
Schwenk, Frieder, Udo Baron, & Klaus Rajewsky. (1995). Acre-transgenic mouse strain for the ubiquitous deletion ofloxP-flanked gene segments including deletion in germ cells. Nucleic Acids Research. 23(24). 5080–5081. 1072 indexed citations breakdown →
20.
Baron, Udo. (1993). Die Wehrideologie der Nationalen Volksarmee der DDR.

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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