Dale R. Wegmann

3.9k total citations · 1 hit paper
41 papers, 3.2k citations indexed

About

Dale R. Wegmann is a scholar working on Genetics, Surgery and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Dale R. Wegmann has authored 41 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Genetics, 25 papers in Surgery and 18 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Dale R. Wegmann's work include Diabetes and associated disorders (31 papers), Pancreatic function and diabetes (24 papers) and Diabetes Management and Research (16 papers). Dale R. Wegmann is often cited by papers focused on Diabetes and associated disorders (31 papers), Pancreatic function and diabetes (24 papers) and Diabetes Management and Research (16 papers). Dale R. Wegmann collaborates with scholars based in United States, Australia and Canada. Dale R. Wegmann's co-authors include Dylan Daniel, Nanette C. Schloot, Kathryn Haskins, George S. Eisenbarth, Liping Yu, Ronald G. Gill, Norio Abiru, John C. Hutton, Dongmei Miao and Hiroaki Moriyama and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and The Journal of Immunology.

In The Last Decade

Dale R. Wegmann

41 papers receiving 3.1k citations

Hit Papers

Prime role for an insulin epitope in the development of t... 2005 2026 2012 2019 2005 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dale R. Wegmann United States 25 2.4k 1.6k 1.5k 1.2k 246 41 3.2k
T L Delovitch Canada 25 1.0k 0.4× 1.5k 0.9× 615 0.4× 408 0.3× 536 2.2× 74 2.5k
Anish Suri United States 25 767 0.3× 1.1k 0.7× 439 0.3× 280 0.2× 284 1.2× 36 1.8k
Stacey N. Walters Australia 21 513 0.2× 1.1k 0.7× 702 0.5× 237 0.2× 307 1.2× 46 2.0k
H Vaughan Australia 13 529 0.2× 414 0.3× 770 0.5× 176 0.1× 376 1.5× 26 1.4k
Guillermo Arreaza Canada 18 678 0.3× 1.0k 0.6× 344 0.2× 234 0.2× 166 0.7× 35 1.5k
Sylvie Trembleau Italy 17 555 0.2× 1.1k 0.7× 198 0.1× 148 0.1× 187 0.8× 28 1.5k
Rima Darwiche Australia 17 499 0.2× 1.3k 0.8× 476 0.3× 221 0.2× 449 1.8× 19 2.2k
Leigh A. Stephens United Kingdom 17 443 0.2× 1.8k 1.1× 274 0.2× 92 0.1× 249 1.0× 18 2.2k
Noelle B. Patterson United States 20 278 0.1× 739 0.5× 482 0.3× 116 0.1× 256 1.0× 30 1.5k
Jinguo Wang Canada 15 271 0.1× 665 0.4× 172 0.1× 121 0.1× 313 1.3× 36 1.2k

Countries citing papers authored by Dale R. Wegmann

Since Specialization
Citations

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

Fields of papers citing papers by Dale R. Wegmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dale R. Wegmann. 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 Dale R. Wegmann. The network helps show where Dale R. Wegmann may publish in the future.

Co-authorship network of co-authors of Dale R. Wegmann

This figure shows the co-authorship network connecting the top 25 collaborators of Dale R. Wegmann. A scholar is included among the top collaborators of Dale R. Wegmann 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 Dale R. Wegmann. Dale R. Wegmann 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.
You, Qiang, Linling Cheng, Timothy P. Reilly, Dale R. Wegmann, & Cynthia Ju. (2006). Role of neutrophils in a mouse model of halothane-induced liver injury. Hepatology. 44(6). 1421–1431. 89 indexed citations
2.
Nakayama, Maki, Norio Abiru, Hiroaki Moriyama, et al.. (2005). Prime role for an insulin epitope in the development of type 1 diabetes in NOD mice. Nature. 435(7039). 220–223. 593 indexed citations breakdown →
3.
Kelemen, Katalin, Peter A. Gottlieb, Amy Putnam, et al.. (2004). HLA-DQ8-Associated T Cell Responses to the Diabetes Autoantigen Phogrin (IA-2β) in Human Prediabetes. The Journal of Immunology. 172(6). 3955–3962. 22 indexed citations
4.
Wheat, William H., et al.. (2004). Increased NF‐κB activity in B cells and bone marrow‐derived dendritic cells from NOD mice. European Journal of Immunology. 34(5). 1395–1404. 45 indexed citations
5.
Hamid, M., Søren Bregenholt, Dale R. Wegmann, et al.. (2002). Genetic fusion of human insulin B‐chain to the B‐subunit of cholera toxin enhances in vitro antigen presentation and induction of bystander suppression in vivo. Immunology. 106(2). 237–245. 27 indexed citations
6.
Kelemen, Katalin, Dale R. Wegmann, & John C. Hutton. (2001). T-Cell Epitope Analysis on the Autoantigen Phogrin (IA-2β) in the Nonobese Diabetic Mouse. Diabetes. 50(8). 1729–1734. 16 indexed citations
7.
Wegmann, Dale R., et al.. (2000). It's Insulin. Journal of Autoimmunity. 15(3). 286–291. 41 indexed citations
8.
Abiru, Norio, Dale R. Wegmann, Eiji Kawasaki, et al.. (2000). Dual Overlapping Peptides Recognized by Insulin Peptide B:9–23 T Cell Receptor AV13S3 T Cell Clones of the NOD Mouse. Journal of Autoimmunity. 14(3). 231–237. 52 indexed citations
9.
Simone, Eric, Dale R. Wegmann, & George S. Eisenbarth. (1999). Immunologic "vaccination" for the prevention of autoimmune diabetes (type 1A).. PubMed. 22 Suppl 2. B7–15. 11 indexed citations
10.
Schloot, Nanette C., Bart O. Roep, Dale R. Wegmann, et al.. (1997). Altered immune response to insulin in newly diagnosed compared to insulin-treated diabetic patients and healthy control subjects. Diabetologia. 40(5). 564–572. 69 indexed citations
12.
Simone, Eric, Liping Yu, Dale R. Wegmann, & George S. Eisenbarth. (1997). T Cell Receptor Gene Polymorphisms Associated with Anti-Insulin, Autoimmune T Cells in Diabetes-Prone NOD Mice. Journal of Autoimmunity. 10(3). 317–321. 19 indexed citations
13.
Wegmann, Dale R., et al.. (1996). Intranasal Administration of Insulin Peptide B: 9–23 Protects NOD Mice from Diabetes. Annals of the New York Academy of Sciences. 778(1). 371–372. 38 indexed citations
14.
Wegmann, Dale R.. (1996). The immune response to islets in experimental diabetes and insulin-dependent diabetes mellitus. Current Opinion in Immunology. 8(6). 860–864. 22 indexed citations
15.
Daniel, Dylan, Ronald G. Gill, Nanette C. Schloot, & Dale R. Wegmann. (1995). Epitope specificity, cytokine production profile and diabetogenic activity of insulin‐specific T cell clones isolated from NOD mice. European Journal of Immunology. 25(4). 1056–1062. 302 indexed citations
16.
Wegmann, Dale R., et al.. (1994). Insulin‐specific T cells are a predominant component of islet infiltrates in pre‐diabetic NOD mice. European Journal of Immunology. 24(8). 1853–1857. 231 indexed citations
17.
Haskins, Kathryn, et al.. (1988). T-lymphocyte clone specific for pancreatic islet antigen. Diabetes. 37(10). 1444–1448. 57 indexed citations
18.
Haskins, Kathryn, Mary Portas, Brenda Bradley, Dale R. Wegmann, & Kevin J. Lafferty. (1988). T-Lymphocyte Clone Specific for Pancreatic Islet Antigen. Diabetes. 37(10). 1444–1448. 170 indexed citations
19.
Nicolas, Jean‐François, et al.. (1987). Relationship of B cell Fc receptors to T cell recognition of Mls antigen. European Journal of Immunology. 17(11). 1561–1565. 28 indexed citations
20.
Morel, Penelope A., et al.. (1986). Interferon-gamma-induced IA expression in WEHI-3 cells is enhanced by the presence of 1,25-dihydroxyvitamin D3.. The Journal of Immunology. 136(6). 2181–2186. 43 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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