Shannon O’Neill

1.1k total citations
18 papers, 855 citations indexed

About

Shannon O’Neill is a scholar working on Immunology, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Shannon O’Neill has authored 18 papers receiving a total of 855 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Immunology, 4 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Molecular Biology. Recurrent topics in Shannon O’Neill's work include T-cell and B-cell Immunology (8 papers), Immunotherapy and Immune Responses (7 papers) and Monoclonal and Polyclonal Antibodies Research (4 papers). Shannon O’Neill is often cited by papers focused on T-cell and B-cell Immunology (8 papers), Immunotherapy and Immune Responses (7 papers) and Monoclonal and Polyclonal Antibodies Research (4 papers). Shannon O’Neill collaborates with scholars based in United States, France and Czechia. Shannon O’Neill's co-authors include Alison Finnegan, Yanxia Cao, Paul D. Doodes, John C. Cambier, Mia J. Smith, Mark J. Shlomchik, Tibor T. Glant, Charles D. Kaplan, Keith M. Hamel and Gábor Hutás and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Experimental Medicine and Immunity.

In The Last Decade

Shannon O’Neill

17 papers receiving 840 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shannon O’Neill United States 12 564 172 151 132 122 18 855
Keith M. Hamel United States 14 620 1.1× 117 0.7× 160 1.1× 176 1.3× 58 0.5× 18 922
Christine Lepajolec France 6 394 0.7× 56 0.3× 245 1.6× 117 0.9× 174 1.4× 9 875
Michelle M. A. Fernando United Kingdom 8 493 0.9× 79 0.5× 280 1.9× 124 0.9× 202 1.7× 13 774
George Treacy United States 14 533 0.9× 172 1.0× 109 0.7× 176 1.3× 86 0.7× 17 860
Joanita Monteiro United States 9 381 0.7× 69 0.4× 146 1.0× 80 0.6× 131 1.1× 13 665
Harold H. Handley United States 14 179 0.3× 193 1.1× 91 0.6× 221 1.7× 61 0.5× 22 560
Erin Janssen United States 17 952 1.7× 64 0.4× 72 0.5× 339 2.6× 188 1.5× 34 1.4k
G Tonietti Italy 19 530 0.9× 108 0.6× 233 1.5× 126 1.0× 94 0.8× 52 1.0k
Brigitte Birebent France 17 604 1.1× 84 0.5× 25 0.2× 249 1.9× 135 1.1× 33 1.1k
KI Welsh United Kingdom 16 465 0.8× 39 0.2× 119 0.8× 104 0.8× 191 1.6× 29 895

Countries citing papers authored by Shannon O’Neill

Since Specialization
Citations

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

Fields of papers citing papers by Shannon O’Neill

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shannon O’Neill. 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 Shannon O’Neill. The network helps show where Shannon O’Neill may publish in the future.

Co-authorship network of co-authors of Shannon O’Neill

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

All Works

18 of 18 papers shown
1.
Shusterman, Roman, et al.. (2025). An active inference strategy for prompting reliable responses from large language models in medical practice. npj Digital Medicine. 8(1). 119–119. 5 indexed citations
2.
Jones, Jasmine, et al.. (2022). Introduction to Radical Empathy in Archival Practice. 3(2). 4 indexed citations
3.
Waters, Allison C., Sara Scherrer, Ashan Veerakumar, et al.. (2020). Effect of Deep Brain Stimulation for Treatment Resistant Depression on Interoceptive Processing: A Pilot Study of the Heartbeat Evoked Potential as Biomarker of Treatment Efficacy. Biological Psychiatry. 87(9). S387–S387. 2 indexed citations
4.
Smith, Mia J., Thomas Packard, Shannon O’Neill, et al.. (2017). Detection and Enrichment of Rare Antigen-specific B Cells for Analysis of Phenotype and Function. Journal of Visualized Experiments. 28 indexed citations
5.
Smith, Mia J., Thomas Packard, Shannon O’Neill, et al.. (2017). Detection and Enrichment of Rare Antigen-specific B Cells for Analysis of Phenotype and Function. Journal of Visualized Experiments. 9 indexed citations
6.
Veselits, Margaret, Azusa Tanaka, Yao-Qing Chen, et al.. (2017). Igβ ubiquitination activates PI3K signals required for endosomal sorting. The Journal of Experimental Medicine. 214(12). 3775–3790. 9 indexed citations
7.
Veselits, Margaret, Azusa Tanaka, Stanley Lipkowitz, et al.. (2014). Recruitment of Cbl-b to B Cell Antigen Receptor Couples Antigen Recognition to Toll-Like Receptor 9 Activation in Late Endosomes. PLoS ONE. 9(3). e89792–e89792. 13 indexed citations
8.
Smith, Mia J., Thomas Packard, Shannon O’Neill, et al.. (2014). Loss of Anergic B Cells in Prediabetic and New-Onset Type 1 Diabetic Patients. Diabetes. 64(5). 1703–1712. 79 indexed citations
9.
O’Neill, Shannon, Andrew Getahun, Stephen B. Gauld, et al.. (2011). Monophosphorylation of CD79a and CD79b ITAM Motifs Initiates a SHIP-1 Phosphatase-Mediated Inhibitory Signaling Cascade Required for B Cell Anergy. Immunity. 35(5). 746–756. 127 indexed citations
10.
O’Neill, Shannon, Edwin Liu, & John C. Cambier. (2009). Change you can B(cell)eive in: recent progress confirms a critical role for B cells in type 1 diabetes. Current Opinion in Endocrinology Diabetes and Obesity. 16(4). 293–298. 21 indexed citations
11.
O’Neill, Shannon, Margaret Veselits, Miao Zhang, et al.. (2009). Endocytic sequestration of the B cell antigen receptor and toll-like receptor 9 in anergic cells. Proceedings of the National Academy of Sciences. 106(15). 6262–6267. 45 indexed citations
12.
O’Neill, Shannon. (2009). Planning of laboratory scale grey water recycling systems. 1 indexed citations
13.
O’Neill, Shannon, Yanxia Cao, Keith M. Hamel, et al.. (2007). Expression of CD80/86 on B Cells Is Essential for Autoreactive T Cell Activation and the Development of Arthritis. The Journal of Immunology. 179(8). 5109–5116. 102 indexed citations
14.
Zhang, Miao, Margaret Veselits, Shannon O’Neill, et al.. (2007). Ubiquitinylation of Igβ Dictates the Endocytic Fate of the B Cell Antigen Receptor. The Journal of Immunology. 179(7). 4435–4443. 52 indexed citations
15.
O’Neill, Shannon, Mark J. Shlomchik, Tibor T. Glant, et al.. (2005). Antigen-Specific B Cells Are Required as APCs and Autoantibody-Producing Cells for Induction of Severe Autoimmune Arthritis. The Journal of Immunology. 174(6). 3781–3788. 158 indexed citations
16.
O’Neill, Shannon. (2003). African American Women and Eating Disturbances: A Meta-Analysis. Journal of Black Psychology. 29(1). 3–16. 42 indexed citations
17.
Kaplan, Charles D., et al.. (2002). Development of Inflammation in Proteoglycan-Induced Arthritis Is Dependent on FcγR Regulation of the Cytokine/Chemokine Environment. The Journal of Immunology. 169(10). 5851–5859. 42 indexed citations
18.
Finnegan, Alison, Michael J. Grusby, Charles D. Kaplan, et al.. (2002). IL-4 and IL-12 Regulate Proteoglycan-Induced Arthritis Through Stat-Dependent Mechanisms. The Journal of Immunology. 169(6). 3345–3352. 116 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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