Eva Kaufmann

3.2k total citations · 1 hit paper
28 papers, 1.6k citations indexed

About

Eva Kaufmann is a scholar working on Immunology, Genetics and Infectious Diseases. According to data from OpenAlex, Eva Kaufmann has authored 28 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Immunology, 8 papers in Genetics and 7 papers in Infectious Diseases. Recurrent topics in Eva Kaufmann's work include Immune responses and vaccinations (8 papers), Immune cells in cancer (6 papers) and Plant and animal studies (5 papers). Eva Kaufmann is often cited by papers focused on Immune responses and vaccinations (8 papers), Immune cells in cancer (6 papers) and Plant and animal studies (5 papers). Eva Kaufmann collaborates with scholars based in Canada, Germany and United States. Eva Kaufmann's co-authors include Maziar Divangahi, Nargis Khan, Erwan Pernet, Luis B. Barreiro, Joaquín Sanz, Alain Pacis, Bruce Mazer, Eisha Ahmed, Anastasia Nijnik and Irah L. King and has published in prestigious journals such as Cell, Nature Communications and Nature Immunology.

In The Last Decade

Eva Kaufmann

23 papers receiving 1.6k citations

Hit Papers

BCG Educates Hematopoietic Stem Cells to Generate Protect... 2018 2026 2020 2023 2018 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eva Kaufmann Canada 16 1.2k 473 340 276 164 28 1.6k
Geoffrey Shellam Australia 25 961 0.8× 219 0.5× 184 0.5× 155 0.6× 39 0.2× 57 2.0k
Shelly J. Robertson United States 28 761 0.6× 1.2k 2.4× 329 1.0× 145 0.5× 29 0.2× 42 2.2k
Sandra Blaise‐Boisseau France 16 163 0.1× 267 0.6× 546 1.6× 187 0.7× 108 0.7× 34 1.2k
Jean‐Nicolas Tournier France 18 266 0.2× 278 0.6× 797 2.3× 293 1.1× 36 0.2× 70 1.2k
Misako Yoneda Japan 24 296 0.2× 770 1.6× 307 0.9× 354 1.3× 8 0.0× 72 1.6k
Kelly S. Hayes United Kingdom 16 213 0.2× 274 0.6× 547 1.6× 69 0.3× 93 0.6× 21 1.2k
Matthew Petitt United States 23 332 0.3× 623 1.3× 306 0.9× 77 0.3× 508 3.1× 28 1.7k
Ignacio Mena United States 26 490 0.4× 888 1.9× 571 1.7× 288 1.0× 12 0.1× 56 2.2k
Suan‐Sin Foo United States 16 220 0.2× 778 1.6× 200 0.6× 49 0.2× 61 0.4× 25 1.3k
Joost H. C. M. Kreijtz Netherlands 31 1.2k 1.0× 703 1.5× 440 1.3× 138 0.5× 7 0.0× 42 2.7k

Countries citing papers authored by Eva Kaufmann

Since Specialization
Citations

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

Fields of papers citing papers by Eva Kaufmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eva Kaufmann

This figure shows the co-authorship network connecting the top 25 collaborators of Eva Kaufmann. A scholar is included among the top collaborators of Eva Kaufmann 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 Eva Kaufmann. Eva Kaufmann 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.
Bhattarai, Salyan, Eva Kaufmann, Feng‐Xia Liang, et al.. (2025). Characterization of SARS‐CoV‐2 Entry Genes in Skeletal Muscle and Impacts of In Vitro Versus In Vivo Infection. Journal of Cachexia Sarcopenia and Muscle. 16(1). e13705–e13705. 2 indexed citations
2.
Park, Kicheon, A. Roger, Amin Reza Nikpoor, et al.. (2025). Basophils activate oncostatin M receptor–expressing vagal sensory neurons. Journal of Allergy and Clinical Immunology. 157(2). 346–362.
4.
Khan, Nargis, Kim A. Tran, Erwan Pernet, et al.. (2025). β-Glucan reprograms neutrophils to promote disease tolerance against influenza A virus. Nature Immunology. 26(2). 174–187. 17 indexed citations
5.
Eichwald, Tuany, A. Roger, Eva Kaufmann, et al.. (2024). Navigating the blurred path of mixed neuroimmune signaling. Journal of Allergy and Clinical Immunology. 153(4). 924–938. 4 indexed citations
6.
Tran, Kim A., Erwan Pernet, Jeffrey Downey, et al.. (2024). BCG immunization induces CX3CR1hi effector memory T cells to provide cross-protection via IFN-γ-mediated trained immunity. Nature Immunology. 25(3). 418–431. 36 indexed citations
7.
Li, Qian, Feng‐Xia Liang, Salyan Bhattarai, et al.. (2024). Dynamic equilibrium of skeletal muscle macrophage ontogeny in the diaphragm during homeostasis, injury, and recovery. Scientific Reports. 14(1). 9132–9132.
8.
Kaufmann, Eva, Andrea Mogas, Mahmood Yaseen Hachim, et al.. (2023). Lung Epithelial Cells from Obese Patients Have Impaired Control of SARS-CoV-2 Infection. International Journal of Molecular Sciences. 24(7). 6729–6729. 1 indexed citations
9.
Pernet, Erwan, Nargis Khan, Joaquín Sanz, et al.. (2023). Human alveolar macrophage metabolism is compromised during Mycobacterium tuberculosis infection. Frontiers in Immunology. 13. 1044592–1044592. 22 indexed citations
10.
Behr, Marcel A., Eva Kaufmann, Jacalyn Duffin, Paul H. Edelstein, & Lalita Ramakrishnan. (2021). Latent Tuberculosis: Two Centuries of Confusion.. Apollo (University of Cambridge). 49 indexed citations
11.
Moorlag, Simone J.C.F.M., Nargis Khan, Boris Novakovic, et al.. (2020). β-Glucan Induces Protective Trained Immunity against Mycobacterium tuberculosis Infection: A Key Role for IL-1. Cell Reports. 31(7). 107634–107634. 217 indexed citations
12.
Khan, Nargis, Jeffrey Downey, Joaquín Sanz, et al.. (2020). M. tuberculosis Reprograms Hematopoietic Stem Cells to Limit Myelopoiesis and Impair Trained Immunity. Cell. 183(3). 752–770.e22. 179 indexed citations
13.
Shah, Kathleen, Ghislaine Fontès, Eva Kaufmann, et al.. (2019). NK cell recruitment limits tissue damage during an enteric helminth infection. Mucosal Immunology. 13(2). 357–370. 20 indexed citations
14.
Divangahi, Maziar, Nargis Khan, & Eva Kaufmann. (2018). Beyond Killing Mycobacterium tuberculosis: Disease Tolerance. Frontiers in Immunology. 9. 2976–2976. 35 indexed citations
15.
Kaufmann, Eva, Joaquín Sanz, Nargis Khan, et al.. (2018). BCG Educates Hematopoietic Stem Cells to Generate Protective Innate Immunity against Tuberculosis. Cell. 172(1-2). 176–190.e19. 804 indexed citations breakdown →
16.
Meunier, Isabelle, Eva Kaufmann, Jeffrey Downey, & Maziar Divangahi. (2017). Unravelling the networks dictating host resistance versus tolerance during pulmonary infections. Cell and Tissue Research. 367(3). 525–536. 15 indexed citations
17.
Krakowka, Steven, Gordon Allan, John Ellis, et al.. (2011). A nine-base nucleotide sequence in the porcine circovirus type 2 (PCV2) nucleocapsid gene determines viral replication and virulence. Virus Research. 164(1-2). 90–99. 30 indexed citations
18.
Kaufmann, Eva & U. Maschwitz. (2006). Ant-gardens of tropical Asian rainforests. Die Naturwissenschaften. 93(5). 216–227. 51 indexed citations
19.
Ito, Fuminori, Rosli Hashim, Sze Huei Yek, et al.. (2004). Spectacular Batesian mimicry in ants. Die Naturwissenschaften. 91(10). 481–484. 25 indexed citations
20.
Maschwitz, U., et al.. (2004). A unique strategy of host colony exploitation in a parasitic ant: workers of Polyrhachis lama rear their brood in neighbouring host nests. Die Naturwissenschaften. 91(1). 40–43. 8 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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