Brian D. Stadinski

1.5k total citations
17 papers, 1.1k citations indexed

About

Brian D. Stadinski is a scholar working on Immunology, Genetics and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Brian D. Stadinski has authored 17 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Immunology, 8 papers in Genetics and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Brian D. Stadinski's work include T-cell and B-cell Immunology (14 papers), Immune Cell Function and Interaction (12 papers) and Diabetes and associated disorders (8 papers). Brian D. Stadinski is often cited by papers focused on T-cell and B-cell Immunology (14 papers), Immune Cell Function and Interaction (12 papers) and Diabetes and associated disorders (8 papers). Brian D. Stadinski collaborates with scholars based in United States, United Kingdom and Japan. Brian D. Stadinski's co-authors include John W. Kappler, Philippa Marrack, Frances Crawford, Eric S. Huseby, George S. Eisenbarth, Li Zhang, Rebecca Smith, Sushil K. Mahata, Richard Reisdorph and Gene Barbour and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Blood and Immunity.

In The Last Decade

Brian D. Stadinski

16 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Brian D. Stadinski United States 14 778 536 284 221 170 17 1.1k
Zhongsheng Sun China 8 829 1.1× 545 1.0× 204 0.7× 146 0.7× 243 1.4× 11 1.3k
Dan Zekzer United States 11 548 0.7× 393 0.7× 221 0.8× 140 0.6× 79 0.5× 11 828
Ruth A. Ettinger United States 19 607 0.8× 328 0.6× 168 0.6× 110 0.5× 274 1.6× 39 1.2k
Stephen T. Ferris United States 16 1.0k 1.3× 420 0.8× 346 1.2× 146 0.7× 230 1.4× 25 1.5k
Nicole H. DeLarato United States 7 449 0.6× 714 1.3× 317 1.1× 163 0.7× 258 1.5× 9 979
Norio Haneji Japan 16 457 0.6× 234 0.4× 91 0.3× 65 0.3× 152 0.9× 27 987
Craig Meagher Canada 13 370 0.5× 236 0.4× 162 0.6× 68 0.3× 159 0.9× 17 629
A Pressey United States 8 456 0.6× 661 1.2× 296 1.0× 178 0.8× 239 1.4× 11 963
Leonie Oxbrow Australia 9 338 0.4× 396 0.7× 276 1.0× 175 0.8× 75 0.4× 10 664
Judith Wilson Australia 7 831 1.1× 425 0.8× 77 0.3× 374 1.7× 107 0.6× 7 1.1k

Countries citing papers authored by Brian D. Stadinski

Since Specialization
Citations

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

Fields of papers citing papers by Brian D. Stadinski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian D. Stadinski. 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 Brian D. Stadinski. The network helps show where Brian D. Stadinski may publish in the future.

Co-authorship network of co-authors of Brian D. Stadinski

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

All Works

17 of 17 papers shown
1.
Stadinski, Brian D., Eric H. Mills, Kosaku Murakami, et al.. (2025). Age-dependent Zap70 expression in thymocytes regulates selection of the neonatal regulatory T cell repertoire. Nature Immunology. 26(12). 2256–2269.
2.
Jones, Michael C., Padma P. Nanaware, Brian D. Stadinski, et al.. (2023). CD4 Effector TCR Avidity for Peptide on APC Determines the Level of Memory Generated. The Journal of Immunology. 210(12). 1950–1961. 6 indexed citations
3.
Stadinski, Brian D., et al.. (2023). I-Ag7 β56/57 polymorphisms regulate non-cognate negative selection to CD4+ T cell orchestrators of type 1 diabetes. Nature Immunology. 24(4). 652–663. 6 indexed citations
4.
Spidale, Nicholas A., Deepali Malhotra, Michela Frascoli, et al.. (2020). Neonatal-derived IL-17 producing dermal γδ T cells are required to prevent spontaneous atopic dermatitis. eLife. 9. 32 indexed citations
5.
Stadinski, Brian D., et al.. (2019). A temporal thymic selection switch and ligand binding kinetics constrain neonatal Foxp3+ Treg cell development. Nature Immunology. 20(8). 1046–1058. 32 indexed citations
6.
Rowe, Jared H., Ottavia M. Delmonte, Sevgi Keleş, et al.. (2018). Patients with CD3G mutations reveal a role for human CD3γ in Treg diversity and suppressive function. Blood. 131(21). 2335–2344. 42 indexed citations
7.
Stadinski, Brian D., Carolyn G. King, Sonja Schallenberg, et al.. (2016). Affinity for self antigen selects Treg cells with distinct functional properties. Nature Immunology. 17(9). 1093–1101. 78 indexed citations
8.
Stadinski, Brian D., Karthik Shekhar, Iria Gómez-Touriño, et al.. (2016). Hydrophobic CDR3 residues promote the development of self-reactive T cells. Nature Immunology. 17(8). 946–955. 103 indexed citations
9.
Stadinski, Brian D., et al.. (2014). Effect of CDR3 Sequences and Distal V Gene Residues in Regulating TCR–MHC Contacts and Ligand Specificity. The Journal of Immunology. 192(12). 6071–6082. 17 indexed citations
10.
Huseby, Eric S., et al.. (2012). Pathogenic CD8 T Cells in Multiple Sclerosis and Its Experimental Models. Frontiers in Immunology. 3. 64–64. 75 indexed citations
11.
Stadinski, Brian D., Rebecca Smith, Bianca Bautista, et al.. (2011). A Role for Differential Variable Gene Pairing in Creating T Cell Receptors Specific for Unique Major Histocompatibility Ligands. Immunity. 35(5). 694–704. 63 indexed citations
12.
Zhang, Li, Brian D. Stadinski, Aaron W. Michels, John W. Kappler, & George S. Eisenbarth. (2011). Immunization with an insulin peptide–MHC complex to prevent type 1 diabetes of NOD mice. Diabetes/Metabolism Research and Reviews. 27(8). 784–789. 14 indexed citations
13.
Crawford, Frances, Brian D. Stadinski, Niyun Jin, et al.. (2011). Specificity and detection of insulin-reactive CD4+T cells in type 1 diabetes in the nonobese diabetic (NOD) mouse. Proceedings of the National Academy of Sciences. 108(40). 16729–16734. 125 indexed citations
14.
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
15.
Stadinski, Brian D., Thomas Delong, Nichole Reisdorph, et al.. (2010). Chromogranin A is an autoantigen in type 1 diabetes. Nature Immunology. 11(3). 225–231. 286 indexed citations
16.
Stadinski, Brian D., John W. Kappler, & George S. Eisenbarth. (2010). Molecular Targeting of Islet Autoantigens. Immunity. 32(4). 446–456. 51 indexed citations
17.
Crawford, Frances, Kimberly R. Jordan, Brian D. Stadinski, et al.. (2006). Use of baculovirus MHC/peptide display libraries to characterize T‐cell receptor ligands. Immunological Reviews. 210(1). 156–170. 54 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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