Ute Wellmann

713 total citations
9 papers, 581 citations indexed

About

Ute Wellmann is a scholar working on Immunology, Rheumatology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Ute Wellmann has authored 9 papers receiving a total of 581 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Immunology, 5 papers in Rheumatology and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Ute Wellmann's work include T-cell and B-cell Immunology (8 papers), Systemic Lupus Erythematosus Research (5 papers) and Monoclonal and Polyclonal Antibodies Research (5 papers). Ute Wellmann is often cited by papers focused on T-cell and B-cell Immunology (8 papers), Systemic Lupus Erythematosus Research (5 papers) and Monoclonal and Polyclonal Antibodies Research (5 papers). Ute Wellmann collaborates with scholars based in Germany, United Kingdom and United States. Ute Wellmann's co-authors include Thomas Winkler, Julia Jellusova, Lars Nitschke, Kerstin Amann, Martin Herrmann, Joachim R. Kalden, Sieglinde Angermüller, Jiquan Zhang, Anja Hoffmann and Burkhard Kneitz and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Immunology and The Journal of Immunology.

In The Last Decade

Ute Wellmann

8 papers receiving 579 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ute Wellmann Germany	6	496	167	156	130	32	9	581
J L Chu United States	7	376 0.8×	203 1.2×	153 1.0×	119 0.9×	5 0.2×	10	525
Anna-Karin B. Lindqvist Sweden	8	245 0.5×	66 0.4×	203 1.3×	90 0.7×	22 0.7×	8	400
Ram Kumar Venigalla United Kingdom	9	425 0.9×	135 0.8×	127 0.8×	19 0.1×	16 0.5×	10	545
Lee Scheinbart United States	2	307 0.6×	215 1.3×	177 1.1×	18 0.1×	16 0.5×	3	542
Christina Gerstner Sweden	9	287 0.6×	125 0.7×	223 1.4×	122 0.9×	15 0.5×	12	500
Rina Kurisu Japan	7	132 0.3×	102 0.6×	128 0.8×	25 0.2×	27 0.8×	9	335
Kristen N. Cordova United States	4	206 0.4×	153 0.9×	109 0.7×	54 0.4×	7 0.2×	5	413
Qinyuan Liao China	10	171 0.3×	166 1.0×	15 0.1×	98 0.8×	18 0.6×	19	326
H.P. Tony Germany	6	260 0.5×	72 0.4×	33 0.2×	103 0.8×	14 0.4×	10	368
Chunmei Wu China	9	145 0.3×	87 0.5×	113 0.7×	15 0.1×	14 0.4×	15	338

Countries citing papers authored by Ute Wellmann

Since Specialization

Citations

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

Fields of papers citing papers by Ute Wellmann

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ute Wellmann

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

All Works

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9 of 9 papers shown

Daniel, Christoph, Fulvia Ferrazzi, Arif B. Ekici, et al.. (2023). Cardiovascular changes in the NZB/W F1 mouse model of lupus nephritis. Frontiers in Cardiovascular Medicine. 10. 1182193–1182193. 3 indexed citations

Schroeder, Kristin, Ute Wellmann, Thomas Winkler, & Martin Herrmann. (2012). Evolution of anti-DNA autoantibodies by somatic hypermutation: evidence for postmutational B cell tolerance. Annals of the Rheumatic Diseases. 71. A32–A32.

Frey, Silke, Ute Wellmann, Vilma Urbonaviciute, et al.. (2011). High frequency of autoantibody‐secreting cells and long‐lived plasma cells within inflamed kidneys of NZB/W F1 lupus mice. European Journal of Immunology. 41(7). 2107–2112. 63 indexed citations

Starke, C., Silke Frey, Ute Wellmann, et al.. (2011). Autoantibody secreting cells and long-lived plasma cells are enriched within inflamed kidneys of NZB/NZW F1 lupus mice and sensitive to bortezomib treatment. Annals of the Rheumatic Diseases. 70. A80–A80. 2 indexed citations

Jellusova, Julia, Ute Wellmann, Kerstin Amann, Thomas Winkler, & Lars Nitschke. (2010). CD22 × Siglec-G Double-Deficient Mice Have Massively Increased B1 Cell Numbers and Develop Systemic Autoimmunity. The Journal of Immunology. 184(7). 3618–3627. 110 indexed citations

Hoffmann, Anja, Sheena C. Kerr, Julia Jellusova, et al.. (2007). Siglec-G is a B1 cell–inhibitory receptor that controls expansion and calcium signaling of the B1 cell population. Nature Immunology. 8(7). 695–704. 160 indexed citations

Wellmann, Ute, et al.. (2005). The evolution of human anti-double-stranded DNA autoantibodies. Proceedings of the National Academy of Sciences. 102(26). 9258–9263. 160 indexed citations

Wellmann, Ute, et al.. (2001). An Ig μ-heavy chain transgene inhibits systemic lupus erythematosus immunopathology in autoimmune (NZB × NZW)F1 mice. International Immunology. 13(12). 1461–1469. 34 indexed citations

Wellmann, Ute, Annick Werner, & Thomas Winkler. (2001). Altered selection processes of B lymphocytes in autoimmune NZB/W mice, despite intact central tolerance against DNA. European Journal of Immunology. 31(9). 2800–2810. 49 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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