Polly Matzinger

27.7k total citations · 10 hit papers
88 papers, 21.7k citations indexed

About

Polly Matzinger is a scholar working on Immunology, Molecular Biology and Genetics. According to data from OpenAlex, Polly Matzinger has authored 88 papers receiving a total of 21.7k indexed citations (citations by other indexed papers that have themselves been cited), including 71 papers in Immunology, 12 papers in Molecular Biology and 11 papers in Genetics. Recurrent topics in Polly Matzinger's work include Immune Cell Function and Interaction (50 papers), T-cell and B-cell Immunology (48 papers) and Immunotherapy and Immune Responses (35 papers). Polly Matzinger is often cited by papers focused on Immune Cell Function and Interaction (50 papers), T-cell and B-cell Immunology (48 papers) and Immunotherapy and Immune Responses (35 papers). Polly Matzinger collaborates with scholars based in United States, Switzerland and United Kingdom. Polly Matzinger's co-authors include Stefania Gallucci, J P Ridge, Francesca Di Rosa, Ephraim J. Fuchs, Seung‐Yong Seong, Martijn P. Lolkema, Michael J. Bevan, Sylvie Guerder, Olivier Lantz and David Gray and has published in prestigious journals such as Nature, Science and Journal of Clinical Investigation.

In The Last Decade

Polly Matzinger

88 papers receiving 21.0k citations

Hit Papers

Tolerance, Danger, and the Extended Family 1977 2026 1993 2009 1994 2002 1998 1999 2004 1000 2.0k 3.0k
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. Tolerance, Danger, and the Extended Family
    1994 3.6k citations Polly Matzinger profile →
  2. The Danger Model: A Renewed Sense of Self
    2002 3.0k citations Polly Matzinger profile →
  3. A conditioned dendritic cell can be a temporal bridge between a CD4+ T-helper and a T-killer cell
    1998 2.0k citations J P Ridge, Francesca Di Rosa et al. Nature profile →
  4. Natural adjuvants: Endogenous activators of dendritic cells
    1999 1.3k citations Stefania Gallucci, Polly Matzinger et al. Nature Medicine profile →
  5. Hydrophobicity: an ancient damage-associated molecular pattern that initiates innate immune responses
    2004 959 citations Polly Matzinger et al. profile →
  6. Danger signals: SOS to the immune system
    2001 919 citations Stefania Gallucci, Polly Matzinger profile →
  7. Neonatal Tolerance Revisited: Turning on Newborn T Cells with Dendritic Cells
    1996 617 citations J P Ridge, Ephraim J. Fuchs et al. profile →
  8. The JAM test A simple assay for DNA fragmentation and cell death
    1991 572 citations Polly Matzinger profile →
  9. An innate sense of danger
    1998 556 citations Polly Matzinger Seminars in Immunology profile →
  10. Why do so many lymphocytes respond to major histocompatibility antigens?
    1977 382 citations Polly Matzinger et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Polly Matzinger United States 51 15.4k 5.3k 2.6k 1.9k 1.7k 88 21.7k
Abul K. Abbas United States 76 17.5k 1.1× 4.8k 0.9× 3.5k 1.3× 2.2k 1.2× 2.0k 1.2× 190 25.9k
Susan J. Fisher United States 84 11.1k 0.7× 7.1k 1.4× 1.6k 0.6× 2.8k 1.5× 1.3k 0.8× 274 28.4k
Paola Ricciardi‐Castagnoli Italy 65 17.7k 1.1× 9.7k 1.8× 2.2k 0.8× 2.8k 1.5× 1.2k 0.7× 179 27.2k
Leonore A. Herzenberg United States 81 10.1k 0.7× 6.2k 1.2× 1.3k 0.5× 1.7k 0.9× 1.2k 0.7× 202 20.1k
Ronald E. Gress United States 70 12.5k 0.8× 3.3k 0.6× 6.5k 2.5× 2.6k 1.4× 1.8k 1.1× 259 20.5k
Karolina Palucka United States 48 14.6k 0.9× 4.8k 0.9× 4.8k 1.9× 1.7k 0.9× 930 0.6× 126 19.0k
Joseph A. Trapani Australia 79 12.3k 0.8× 8.8k 1.7× 6.3k 2.4× 2.5k 1.3× 1.8k 1.1× 337 22.5k
Smith Rjh Sweden 68 9.3k 0.6× 8.5k 1.6× 1.5k 0.6× 1.8k 0.9× 3.2k 1.9× 723 20.5k
Paul M. Allen United States 79 16.6k 1.1× 7.5k 1.4× 3.6k 1.4× 1.6k 0.8× 1.5k 0.9× 209 24.8k
Michael C. Carroll United States 89 16.1k 1.0× 5.5k 1.0× 2.1k 0.8× 2.2k 1.2× 1.8k 1.0× 265 26.8k

Countries citing papers authored by Polly Matzinger

Since Specialization
Citations

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

Fields of papers citing papers by Polly Matzinger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Polly Matzinger

This figure shows the co-authorship network connecting the top 25 collaborators of Polly Matzinger. A scholar is included among the top collaborators of Polly Matzinger 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 Polly Matzinger. Polly Matzinger 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.
Pérez‐Díez, Ainhoa, et al.. (2022). Neoantigen Presentation and IFNγ Signaling on the Same Tumor-associated Macrophage are Necessary for CD4 T Cell–mediated Antitumor Activity in Mice. Cancer Research Communications. 2(5). 316–329. 12 indexed citations
2.
Morgun, Andrey, Amiran Dzutsev, Xiaoxi Dong, et al.. (2015). Uncovering effects of antibiotics on the host and microbiota using transkingdom gene networks. Gut. 64(11). 1732–1743. 228 indexed citations
3.
Shulzhenko, Natalia, Anatoly Yambartsev, Mark Rochman, et al.. (2013). Gene network reconstruction reveals cell cycle and antiviral genes as major drivers of cervical cancer. Nature Communications. 4(1). 1806–1806. 61 indexed citations
4.
Helft, Julie, Alexandra Jacquet, Nathalie T. Joncker, et al.. (2008). Antigen-specific T-T interactions regulate CD4 T-cell expansion. Blood. 112(4). 1249–1258. 54 indexed citations
5.
Pérez‐Díez, Ainhoa, Paul J. Spiess, Nicholas P. Restifo, Polly Matzinger, & Francesco M. Marincola. (2002). Intensity of the Vaccine-Elicited Immune Response Determines Tumor Clearance. The Journal of Immunology. 168(1). 338–347. 68 indexed citations
6.
Alpan, Oral, et al.. (2001). The Role of Dendritic Cells, B Cells, and M Cells in Gut-Oriented Immune Responses. The Journal of Immunology. 166(8). 4843–4852. 132 indexed citations
7.
Anderson, Colin C., Joseph M. Carroll, Stefania Gallucci, et al.. (2001). Testing Time-, Ignorance-, and Danger-Based Models of Tolerance. The Journal of Immunology. 166(6). 3663–3671. 56 indexed citations
8.
Matzinger, Polly. (2001). Essay 1: The Danger Model in Its Historical Context. Scandinavian Journal of Immunology. 54(1-2). 4–9. 119 indexed citations
9.
Anderson, Colin C. & Polly Matzinger. (2001). Immunity or tolerance: Opposite outcomes of microchimerism from skin grafts. Nature Medicine. 7(1). 80–87. 87 indexed citations
10.
Rosa, Francesca Di & Polly Matzinger. (1996). Long-lasting CD8 T cell memory in the absence of CD4 T cells or B cells.. The Journal of Experimental Medicine. 183(5). 2153–2163. 90 indexed citations
11.
Fuchs, Ephraim J. & Polly Matzinger. (1996). Is cancer dangerous to the immune system?. Seminars in Immunology. 8(5). 271–280. 217 indexed citations
12.
Epstein, M., Francesca Di Rosa, Dragana Janković, Alan Sher, & Polly Matzinger. (1995). Successful T cell priming in B cell-deficient mice.. The Journal of Experimental Medicine. 182(4). 915–922. 250 indexed citations
13.
Bonomo, Adriana & Polly Matzinger. (1993). Thymus epithelium induces tissue-specific tolerance.. The Journal of Experimental Medicine. 177(4). 1153–1164. 90 indexed citations
14.
Bendelac, Albert, Polly Matzinger, R A Seder, W E Paul, & R H Schwartz. (1992). Activation events during thymic selection.. The Journal of Experimental Medicine. 175(3). 731–742. 292 indexed citations
15.
Gray, David & Polly Matzinger. (1991). T cell memory is short-lived in the absence of antigen.. The Journal of Experimental Medicine. 174(5). 969–974. 309 indexed citations
16.
Guerder, Sylvie & Polly Matzinger. (1989). Activation versus Tolerance: A Decision Made by T Helper Cells. Cold Spring Harbor Symposia on Quantitative Biology. 54(0). 799–805. 39 indexed citations
17.
Matzinger, Polly & Sylvie Guerder. (1989). Does T-cell tolerance require a dedicated antigen-presenting cell?. Nature. 338(6210). 74–76. 226 indexed citations
18.
Vidović, Damir & Polly Matzinger. (1988). Unresponsiveness to a foreign antigen can be caused by self-tolerance. Nature. 336(6196). 222–225. 104 indexed citations
19.
Lassila, Olli, Olli Vainio, & Polly Matzinger. (1988). Can B cells turn on virgin T cells?. Nature. 334(6179). 253–255. 158 indexed citations
20.
Shih, Wei‐Liang, Polly Matzinger, Susan L. Swain, & R W Dutton. (1980). Analysis of histocompatibility requirements for proliferative and helper T cell activity. T cell populations depleted of alloreactive cells by negative selection.. The Journal of Experimental Medicine. 152(5). 1311–1328. 19 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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