George S. Eisenbarth

52.6k total citations · 14 hit papers
510 papers, 37.0k citations indexed

About

George S. Eisenbarth is a scholar working on Genetics, Surgery and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, George S. Eisenbarth has authored 510 papers receiving a total of 37.0k indexed citations (citations by other indexed papers that have themselves been cited), including 406 papers in Genetics, 318 papers in Surgery and 276 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in George S. Eisenbarth's work include Diabetes and associated disorders (399 papers), Pancreatic function and diabetes (308 papers) and Diabetes Management and Research (219 papers). George S. Eisenbarth is often cited by papers focused on Diabetes and associated disorders (399 papers), Pancreatic function and diabetes (308 papers) and Diabetes Management and Research (219 papers). George S. Eisenbarth collaborates with scholars based in United States, Australia and Italy. George S. Eisenbarth's co-authors include Mark A. Atkinson, Liping Yu, Marian Rewers, Aaron W. Michels, Jeffrey S. Flier, Lisa H. Underhill, Peter A. Gottlieb, Edwin Liu, Jeffrey A. Bluestone and Kevan C. Herold and has published in prestigious journals such as Nature, Science and New England Journal of Medicine.

In The Last Decade

George S. Eisenbarth

507 papers receiving 35.5k citations

Hit Papers

Type 1 diabetes 1979 2026 1994 2010 2013 1986 2001 2004 2010 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. Type 1 diabetes
    2013 1.8k citations George S. Eisenbarth, Aaron W. Michels et al. profile →
  2. Type I Diabetes Mellitus
    1986 1.3k citations George S. Eisenbarth et al. profile →
  3. Type 1 diabetes: new perspectives on disease pathogenesis and treatment
    2001 1.1k citations George S. Eisenbarth et al. profile →
  4. A functional variant of lymphoid tyrosine phosphatase is associated with type I diabetes
    2004 1.0k citations George S. Eisenbarth et al. profile →
  5. Genetics, pathogenesis and clinical interventions in type 1 diabetes
    2010 917 citations George S. Eisenbarth et al. profile →
  6. Monoclonal antibody to a plasma membrane antigen of neurons.
    1979 847 citations George S. Eisenbarth, F S Walsh et al. Proceedings of the National Academy of Sciences profile →
  7. Seroconversion to Multiple Islet Autoantibodies and Risk of Progression to Diabetes in Children
    2013 833 citations Marian Rewers, George S. Eisenbarth et al. JAMA profile →
  8. The cation efflux transporter ZnT8 (Slc30A8) is a major autoantigen in human type 1 diabetes
    2007 723 citations Janet M. Wenzlau, Kirstine Juhl et al. Proceedings of the National Academy of Sciences profile →
  9. The insulin gene is transcribed in the human thymus and transcription levels correlate with allelic variation at the INS VNTR-IDDM2 susceptibility locus for type 1 diabetes
    1997 723 citations Alberto Pugliese, George S. Eisenbarth et al. profile →
  10. Prediction of Type I Diabetes in First-Degree Relatives Using a Combination of Insulin, GAD, and ICA512bdc/IA-2 Autoantibodies
    1996 623 citations Eiji Kawasaki, Liping Yu et al. profile →
  11. Prime role for an insulin epitope in the development of type 1 diabetes in NOD mice
    2005 593 citations Maki Nakayama, Norio Abiru et al. profile →
  12. Type-I Diabetes: A Chronic Autoimmune Disease of Human, Mouse, and Rat
    1990 568 citations George S. Eisenbarth et al. profile →
  13. Suppression of diabetes in nonobese diabetic mice by oral administration of porcine insulin.
    1991 461 citations George S. Eisenbarth et al. Proceedings of the National Academy of Sciences profile →
  14. Characterization of a monoclonal antibody (4F2) that binds to human monocytes and to a subset of activated lymphocytes.
    1981 402 citations George S. Eisenbarth et al. The Journal of Immunology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
George S. Eisenbarth United States 94 26.0k 19.6k 18.6k 9.0k 4.6k 510 37.0k
Åke Lernmark United States 80 17.2k 0.7× 14.7k 0.7× 13.4k 0.7× 3.9k 0.4× 4.1k 0.9× 710 26.1k
Ezio Bonifacio Germany 78 13.9k 0.5× 12.2k 0.6× 10.8k 0.6× 3.6k 0.4× 2.3k 0.5× 354 20.4k
Kevan C. Herold United States 73 10.5k 0.4× 9.1k 0.5× 8.6k 0.5× 6.0k 0.7× 2.7k 0.6× 278 20.0k
Leonard C. Harrison Australia 69 7.1k 0.3× 5.5k 0.3× 4.5k 0.2× 5.3k 0.6× 3.0k 0.7× 329 14.9k
Flemming Pociot Denmark 61 7.2k 0.3× 5.2k 0.3× 3.9k 0.2× 4.5k 0.5× 4.6k 1.0× 326 16.2k
Jørn Nerup Denmark 64 7.8k 0.3× 6.1k 0.3× 5.7k 0.3× 3.6k 0.4× 2.5k 0.5× 256 15.0k
Burkhard Göke Germany 72 3.2k 0.1× 6.1k 0.3× 6.4k 0.3× 2.7k 0.3× 6.0k 1.3× 423 20.1k
Paolo Pozzilli Italy 62 6.4k 0.2× 5.6k 0.3× 6.9k 0.4× 1.6k 0.2× 2.4k 0.5× 443 14.3k
Noel K. Maclaren United States 54 7.6k 0.3× 5.0k 0.3× 6.4k 0.3× 2.9k 0.3× 1.3k 0.3× 205 12.2k
Clive Wasserfall United States 60 5.1k 0.2× 3.7k 0.2× 3.0k 0.2× 2.8k 0.3× 3.7k 0.8× 217 11.7k

Countries citing papers authored by George S. Eisenbarth

Since Specialization
Citations

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

Fields of papers citing papers by George S. Eisenbarth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by George S. Eisenbarth. 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 George S. Eisenbarth. The network helps show where George S. Eisenbarth may publish in the future.

Co-authorship network of co-authors of George S. Eisenbarth

This figure shows the co-authorship network connecting the top 25 collaborators of George S. Eisenbarth. A scholar is included among the top collaborators of George S. Eisenbarth 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 George S. Eisenbarth. George S. Eisenbarth 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.
Zhang, Li, Frances Crawford, Liping Yu, et al.. (2014). Monoclonal antibody blocking the recognition of an insulin peptide–MHC complex modulates type 1 diabetes. Proceedings of the National Academy of Sciences. 111(7). 2656–2661. 56 indexed citations
2.
Roep, Bart O., Nanette Solvason, Peter A. Gottlieb, et al.. (2013). Plasmid-Encoded Proinsulin Preserves C-Peptide While Specifically Reducing Proinsulin-Specific CD8 + T Cells in Type 1 Diabetes. Science Translational Medicine. 5(191). 191ra82–191ra82. 127 indexed citations
3.
Baker, Peter R., P. Fain, Heinrich Kahles, et al.. (2012). Genetic Determinants of 21-Hydroxylase Autoantibodies Amongst Patients of the Type 1 Diabetes Genetics Consortium. The Journal of Clinical Endocrinology & Metabolism. 97(8). E1573–E1578. 7 indexed citations
4.
Nakahara, Mami, Yuji Nagayama, Tatsuki Ichikawa, et al.. (2011). The effect of regulatory T-cell depletion on the spectrum of organ-specific autoimmune diseases in nonobese diabetic mice at different ages. Autoimmunity. 44(6). 504–510. 19 indexed citations
5.
Stadinski, Brian D., Li Zhang, Frances Crawford, et al.. (2010). Diabetogenic T cells recognize insulin bound to IA g7 in an unexpected, weakly binding register. Proceedings of the National Academy of Sciences. 107(24). 10978–10983. 164 indexed citations
6.
Burton, Amanda R., Zachary C. Baquet, George S. Eisenbarth, et al.. (2010). Central Nervous System Destruction Mediated by Glutamic Acid Decarboxylase-Specific CD4+ T Cells. The Journal of Immunology. 184(9). 4863–4870. 54 indexed citations
7.
Babaya, Naru, Edwin Liu, Dongmei Miao, et al.. (2009). Murine High Specificity/Sensitivity Competitive Europium Insulin Autoantibody Assay. Diabetes Technology & Therapeutics. 11(4). 227–233. 16 indexed citations
8.
Regnault, Béatrice, José Osorio y Fortéa, Dongmei Miao, George S. Eisenbarth, & Evie Melanitou. (2009). Early over expression of messenger RNA for multiple genes, including insulin, in the Pancreatic Lymph Nodes of NOD mice is associated with Islet Autoimmunity. BMC Medical Genomics. 2(1). 63–63. 12 indexed citations
9.
Kobayashi, Masakazu, Jean Jasinski, Edwin Liu, et al.. (2008). Conserved T cell receptor α-chain induces insulin autoantibodies. Proceedings of the National Academy of Sciences. 105(29). 10090–10094. 22 indexed citations
10.
Baschal, Erin E. & George S. Eisenbarth. (2008). Extreme genetic risk for type 1A diabetes in the post-genome era. Journal of Autoimmunity. 31(1). 1–6. 40 indexed citations
11.
Liu, Edwin, Marcella Li, Lisa M. Emery, et al.. (2007). Natural History of Antibodies to Deamidated Gliadin Peptides and Transglutaminase in Early Childhood Celiac Disease. Journal of Pediatric Gastroenterology and Nutrition. 45(3). 293–300. 86 indexed citations
12.
Wenzlau, Janet M., Kirstine Juhl, Liping Yu, et al.. (2007). The cation efflux transporter ZnT8 (Slc30A8) is a major autoantigen in human type 1 diabetes. Proceedings of the National Academy of Sciences. 104(43). 17040–17045. 723 indexed citations breakdown →
13.
Norris, Jill M., Xiang Yin, Molly M. Lamb, et al.. (2007). Omega-3 Polyunsaturated Fatty Acid Intake and Islet Autoimmunity in Children at Increased Risk for Type 1 Diabetes. JAMA. 298(12). 1420–1420. 212 indexed citations
14.
Aly, Theresa A., Akane Ide, Mohamed M. Jahromi, et al.. (2006). Extreme genetic risk for type 1A diabetes. Proceedings of the National Academy of Sciences. 103(38). 14074–14079. 152 indexed citations
15.
Kobayashi, M, Norio Abiru, Keiko Fukushima, et al.. (2005). NASAL ADMINISTRATION OF AN ALTERED PEPTIDE LIGAND OF INSULIN PEPTIDE B:9-23 WITH CHOLERA TOXIN SUPPRESSES THE EXPRESSION OF INSULIN AUTOANTIBODIES AND PREVENTS DIABETES IN THE NOD MOUSE. Endocrine Journal. 52. 108. 1 indexed citations
16.
Devendra, Devasenan & George S. Eisenbarth. (2004). Interferon alpha—a potential link in the pathogenesis of viral-induced type 1 diabetes and autoimmunity. Clinical Immunology. 111(3). 225–233. 83 indexed citations
17.
Tiberti, Claudio, Fei Bao, Margherita Bonamico, et al.. (2003). Celiac disease-associated transglutaminase autoantibody target domains at diagnosis are age and sex dependent. Clinical Immunology. 109(3). 318–324. 7 indexed citations
18.
Pugliese, Alberto, Teodorica L. Bugawan, Z Awdeh, et al.. (1994). Two subsets of HLA-DQA1 alleles mark phenotypic variation in levels of insulin autoantibodies in first degree relatives at risk for insulin-dependent diabetes.. Journal of Clinical Investigation. 93(6). 2447–2452. 29 indexed citations
19.
Bækkeskov, Steinunn, Maria A. Landin, Jørgen Kvist Kristensen, et al.. (1987). Antibodies to a 64,000 Mr human islet cell antigen precede the clinical onset of insulin-dependent diabetes.. Journal of Clinical Investigation. 79(3). 926–934. 262 indexed citations
20.
Eisenbarth, George S., F S Walsh, & Marshall W. Nirenberg. (1979). Monoclonal antibody to a plasma membrane antigen of neurons.. Proceedings of the National Academy of Sciences. 76(10). 4913–4917. 847 indexed citations breakdown →

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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