Eric J. Wigton

506 total citations
10 papers, 373 citations indexed

About

Eric J. Wigton is a scholar working on Immunology, Molecular Biology and Cancer Research. According to data from OpenAlex, Eric J. Wigton has authored 10 papers receiving a total of 373 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Immunology, 3 papers in Molecular Biology and 3 papers in Cancer Research. Recurrent topics in Eric J. Wigton's work include Immune Cell Function and Interaction (5 papers), T-cell and B-cell Immunology (3 papers) and MicroRNA in disease regulation (3 papers). Eric J. Wigton is often cited by papers focused on Immune Cell Function and Interaction (5 papers), T-cell and B-cell Immunology (3 papers) and MicroRNA in disease regulation (3 papers). Eric J. Wigton collaborates with scholars based in United States, Japan and Netherlands. Eric J. Wigton's co-authors include Jordan Jacobelli, Todd C. Metzger, David J. Erle, Bruno Kyewski, Joshua L. Pollack, Adam Fries, Jakob von Moltke, Audrey V. Parent, Imran S. Khan and Corey N. Miller and has published in prestigious journals such as Nature, The Journal of Experimental Medicine and The Journal of Immunology.

In The Last Decade

Eric J. Wigton

10 papers receiving 371 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Eric J. Wigton United States	7	185	124	66	56	47	10	373
Irina Proekt United States	8	313 1.7×	151 1.2×	18 0.3×	141 2.5×	63 1.3×	13	528
Andréa Alex Schiavo Belgium	11	56 0.3×	232 1.9×	91 1.4×	50 0.9×	55 1.2×	13	404
Kelsey E. Quinn United States	10	174 0.9×	207 1.7×	47 0.7×	11 0.2×	64 1.4×	20	444
Denise Sickert Switzerland	9	163 0.9×	103 0.8×	15 0.2×	21 0.4×	69 1.5×	14	363
Nahoko Tomonobu Japan	9	104 0.6×	184 1.5×	80 1.2×	16 0.3×	104 2.2×	24	350
Aya Ishii Japan	11	41 0.2×	140 1.1×	70 1.1×	31 0.6×	74 1.6×	27	364
Mayuki Watanabe Japan	7	156 0.8×	115 0.9×	21 0.3×	20 0.4×	25 0.5×	8	332
Mathias Hauri‐Hohl Switzerland	11	260 1.4×	134 1.1×	12 0.2×	54 1.0×	74 1.6×	22	469
K Masuda Japan	6	156 0.8×	127 1.0×	16 0.2×	53 0.9×	122 2.6×	6	429
Katrina L. Scarff Australia	7	65 0.4×	146 1.2×	54 0.8×	10 0.2×	39 0.8×	9	312

Countries citing papers authored by Eric J. Wigton

Since Specialization

Citations

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

Fields of papers citing papers by Eric J. Wigton

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eric J. Wigton

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

All Works

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10 of 10 papers shown

Mathewson, Nathan D., Kelly D. Moynihan, Wei Chen, et al.. (2022). Abstract 561: CAR-targeted IL-2 drives selective CAR-T cell expansion and improves anti-tumor efficacy. Cancer Research. 82(12_Supplement). 561–561. 1 indexed citations

Wigton, Eric J., Yohei Mikami, Carlos A. Castellanos, et al.. (2021). MicroRNA-directed pathway discovery elucidates an miR-221/222–mediated regulatory circuit in class switch recombination. The Journal of Experimental Medicine. 218(11). 11 indexed citations

Wigton, Eric J. & K. Mark Ansel. (2021). Noncoding RNAs in B cell responses. RNA Biology. 18(5). 633–639. 4 indexed citations

Coffre, Maryaline, Tenny Mudianto, Marisella Panduro, et al.. (2020). miR-29 Sustains B Cell Survival and Controls Terminal Differentiation via Regulation of PI3K Signaling. Cell Reports. 33(9). 108436–108436. 21 indexed citations

Wigton, Eric J., Anthony DeFranco, & K. Mark Ansel. (2019). Antigen Complexed with a TLR9 Agonist Bolsters c-Myc and mTORC1 Activity in Germinal Center B Lymphocytes. ImmunoHorizons. 3(8). 389–401. 2 indexed citations

Gagnon, John D, Robin Kageyama, Hesham M. Shehata, et al.. (2019). miR-15/16 Restrain Memory T Cell Differentiation, Cell Cycle, and Survival. Cell Reports. 28(8). 2169–2181.e4. 63 indexed citations

Miller, Corey N., Irina Proekt, Jakob von Moltke, et al.. (2018). Thymic tuft cells promote an IL-4-enriched medulla and shape thymocyte development. Nature. 559(7715). 627–631. 206 indexed citations

Wigton, Eric J., et al.. (2018). The Formin mDia1 Regulates Acute Lymphoblastic Leukemia Engraftment, Migration, and Progression in vivo. Frontiers in Oncology. 8. 389–389. 11 indexed citations

Wigton, Eric J., et al.. (2016). Myosin-IIA regulates leukemia engraftment and brain infiltration in a mouse model of acute lymphoblastic leukemia. Journal of Leukocyte Biology. 100(1). 143–153. 25 indexed citations

10.

Lindsay, Robin S., Kaitlin Corbin, Matthew J. Gebert, et al.. (2014). Antigen Recognition in the Islets Changes with Progression of Autoimmune Islet Infiltration. The Journal of Immunology. 194(2). 522–530. 29 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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