Eric Fagerberg

1.1k total citations · 1 hit paper
9 papers, 435 citations indexed

About

Eric Fagerberg is a scholar working on Immunology, Oncology and Infectious Diseases. According to data from OpenAlex, Eric Fagerberg has authored 9 papers receiving a total of 435 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Immunology, 5 papers in Oncology and 1 paper in Infectious Diseases. Recurrent topics in Eric Fagerberg's work include Immune Cell Function and Interaction (6 papers), Immunotherapy and Immune Responses (5 papers) and Cancer Immunotherapy and Biomarkers (4 papers). Eric Fagerberg is often cited by papers focused on Immune Cell Function and Interaction (6 papers), Immunotherapy and Immune Responses (5 papers) and Cancer Immunotherapy and Biomarkers (4 papers). Eric Fagerberg collaborates with scholars based in United States, India and China. Eric Fagerberg's co-authors include Nikhil S. Joshi, Can Cui, Martina Damo, Gena G. Foster, Brittany Fitzgerald, Kelli A. Connolly, Julie F. Cheung, Ping-Min Chen, Shuting Chen and Stephanie C. Eisenbarth and has published in prestigious journals such as Nature, Cell and Frontiers in Immunology.

In The Last Decade

Eric Fagerberg

7 papers receiving 432 citations

Hit Papers

Neoantigen-driven B cell and CD4 T follicular helper cell... 2021 2026 2022 2024 2021 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eric Fagerberg United States 6 282 228 137 83 53 9 435
Jingya Qiu United States 3 272 1.0× 243 1.1× 146 1.1× 61 0.7× 59 1.1× 4 424
Kelli A. Connolly United States 6 312 1.1× 305 1.3× 113 0.8× 52 0.6× 56 1.1× 13 479
Shalom Lerrer United States 9 226 0.8× 278 1.2× 202 1.5× 122 1.5× 51 1.0× 17 507
Changchang Lu China 9 247 0.9× 260 1.1× 131 1.0× 74 0.9× 58 1.1× 20 448
Sheryl Kunning United States 7 305 1.1× 344 1.5× 108 0.8× 57 0.7× 71 1.3× 10 503
Jessica D. Weaver United States 6 377 1.3× 302 1.3× 106 0.8× 81 1.0× 32 0.6× 9 514
Ravindra Uppaluri United States 10 390 1.4× 313 1.4× 159 1.2× 62 0.7× 44 0.8× 25 590
Qinglin Fei China 8 185 0.7× 210 0.9× 134 1.0× 52 0.6× 40 0.8× 16 362
Jenny Lazarus United States 7 162 0.6× 254 1.1× 121 0.9× 44 0.5× 46 0.9× 11 348
Hassan Sadozai Canada 10 233 0.8× 230 1.0× 101 0.7× 44 0.5× 61 1.2× 15 422

Countries citing papers authored by Eric Fagerberg

Since Specialization
Citations

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

Fields of papers citing papers by Eric Fagerberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eric Fagerberg

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

All Works

9 of 9 papers shown
1.
Venkat, Aarthi, et al.. (2024). Mapping the gene space at single-cell resolution with gene signal pattern analysis. Nature Computational Science. 4(12). 955–977.
2.
Strine, Madison S., Eric Fagerberg, Renata B. Filler, et al.. (2024). Intestinal tuft cell immune privilege enables norovirus persistence. Science Immunology. 9(93). eadi7038–eadi7038. 7 indexed citations
3.
Damo, Martina, Noah I. Hornick, Aarthi Venkat, et al.. (2023). PD-1 maintains CD8 T cell tolerance towards cutaneous neoantigens. Nature. 619(7968). 151–159. 40 indexed citations
4.
Fitzgerald, Brittany, Kelli A. Connolly, Can Cui, et al.. (2021). A mouse model for the study of anti-tumor T cell responses in Kras-driven lung adenocarcinoma. Cell Reports Methods. 1(5). 100080–100080. 17 indexed citations
5.
Cui, Can, Jiawei Wang, Eric Fagerberg, et al.. (2021). Neoantigen-driven B cell and CD4 T follicular helper cell collaboration promotes anti-tumor CD8 T cell responses. Cell. 184(25). 6101–6118.e13. 280 indexed citations breakdown →
6.
Fitzgerald, Brittany, Kelli A. Connolly, Can Cui, et al.. (2021). A Novel Mouse Model for the Study of Anti-Tumor T Cell Responses in Kras Driven Lung Adenocarcinoma. SSRN Electronic Journal.
7.
Cui, Can, Jiawei Wang, Kelli A. Connolly, et al.. (2020). Neoantigen Driven B Cell and CD4+ T Follicular Helper Cell Collaboration Promotes Robust Anti-Tumor CD8+ T Cell Responses. SSRN Electronic Journal. 3 indexed citations
8.
Pobezinskaya, Elena L., et al.. (2019). Survival of Naïve T Cells Requires the Expression of Let-7 miRNAs. Frontiers in Immunology. 10. 955–955. 11 indexed citations
9.
Wells, Alexandria, Keith A. Daniels, Eric Fagerberg, et al.. (2017). Modulation of let-7 miRNAs controls the differentiation of effector CD8 T cells. eLife. 6. 77 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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