Eva Bartok

4.0k total citations · 1 hit paper
35 papers, 2.1k citations indexed

About

Eva Bartok is a scholar working on Immunology, Molecular Biology and Infectious Diseases. According to data from OpenAlex, Eva Bartok has authored 35 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Immunology, 19 papers in Molecular Biology and 4 papers in Infectious Diseases. Recurrent topics in Eva Bartok's work include interferon and immune responses (18 papers), Inflammasome and immune disorders (13 papers) and Immune Response and Inflammation (11 papers). Eva Bartok is often cited by papers focused on interferon and immune responses (18 papers), Inflammasome and immune disorders (13 papers) and Immune Response and Inflammation (11 papers). Eva Bartok collaborates with scholars based in Germany, Belgium and United States. Eva Bartok's co-authors include Veit Hornung, Franz Bauernfeind, Gunther Hartmann, Jonathan L. Schmid‐Burgk, Gabriel Núñez, Luigi Franchi, Tobias Schmidt, Moritz M. Gaidt, Andrea Ablasser and Sarah Kim-Hellmuth and has published in prestigious journals such as Angewandte Chemie International Edition, Immunity and The Journal of Immunology.

In The Last Decade

Eva Bartok

30 papers receiving 2.1k citations

Hit Papers

Cutting Edge: Reactive Oxygen Species Inhibitors Block Pr... 2011 2026 2016 2021 2011 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eva Bartok Germany 16 1.5k 898 214 208 195 35 2.1k
Alessandra Pontillo Brazil 29 1.7k 1.2× 1.2k 1.3× 178 0.8× 327 1.6× 172 0.9× 91 2.5k
Takuma Misawa Japan 15 1.0k 0.7× 1.0k 1.2× 165 0.8× 231 1.1× 127 0.7× 20 1.9k
Guangxun Meng China 22 1.2k 0.8× 1.3k 1.5× 206 1.0× 408 2.0× 120 0.6× 32 2.4k
Michihiro Takahama Japan 12 1000 0.7× 913 1.0× 155 0.7× 288 1.4× 133 0.7× 21 1.8k
Guangxun Meng China 26 1.6k 1.0× 895 1.0× 367 1.7× 366 1.8× 110 0.6× 59 2.4k
Gabriel Sollberger Germany 13 1.3k 0.9× 1.4k 1.5× 135 0.6× 188 0.9× 142 0.7× 16 2.1k
Sebastian Rühl Switzerland 9 2.4k 1.6× 1.1k 1.2× 128 0.6× 230 1.1× 411 2.1× 11 2.7k
Salina Louie United States 9 2.3k 1.6× 1.2k 1.3× 108 0.5× 247 1.2× 281 1.4× 14 2.7k
Irma B. Stowe United States 9 1.5k 1.0× 861 1.0× 78 0.4× 194 0.9× 231 1.2× 9 1.9k
Paras Anand United Kingdom 24 2.1k 1.4× 1.3k 1.5× 232 1.1× 499 2.4× 146 0.7× 40 2.9k

Countries citing papers authored by Eva Bartok

Since Specialization
Citations

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

Fields of papers citing papers by Eva Bartok

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eva Bartok

This figure shows the co-authorship network connecting the top 25 collaborators of Eva Bartok. A scholar is included among the top collaborators of Eva Bartok 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 Bartok. Eva Bartok 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
2.
Holdenrieder, Stefan, Stephan Garbe, Rayk Behrendt, et al.. (2023). RIG-I immunotherapy overcomes radioresistance in p53-positive malignant melanoma. Journal of Molecular Cell Biology. 15(1). 12 indexed citations
3.
Zsurka, Gábor, Kerstin Hallmann, Niels Hansen, et al.. (2023). Loss of the Immunomodulatory Transcription Factor BATF2 in Humans Is Associated with a Neurological Phenotype. Cells. 12(2). 227–227. 4 indexed citations
4.
Bartok, Eva, et al.. (2023). Unexpected bonds: ubiquitin-like conjugation of cGAS/CD-NTases supports their enzymatic activity and antiphage defense. Signal Transduction and Targeted Therapy. 8(1). 308–308. 2 indexed citations
5.
6.
Bartok, Eva, et al.. (2022). Innate sensing of mRNA vaccines. Current Opinion in Immunology. 79. 102249–102249. 9 indexed citations
7.
Dolscheid‐Pommerich, Ramona, Eva Bartok, Marcel Renn, et al.. (2021). Correlation between a quantitative anti‐SARS‐CoV‐2 IgG ELISA and neutralization activity. Journal of Medical Virology. 94(1). 388–392. 75 indexed citations
8.
Herzner, Anna‐Maria, Martin Schlee, & Eva Bartok. (2021). The many faces of cGAS: how cGAS activation is controlled in the cytosol, the nucleus, and during mitosis. Signal Transduction and Targeted Therapy. 6(1). 260–260. 7 indexed citations
9.
Renn, Marcel, Eva Bartok, Thomas Zillinger, Gunther Hartmann, & Rayk Behrendt. (2021). Animal models of SARS-CoV-2 and COVID-19 for the development of prophylactic and therapeutic interventions. Pharmacology & Therapeutics. 228. 107931–107931. 15 indexed citations
10.
Bartok, Eva & Gunther Hartmann. (2020). Immune Sensing Mechanisms that Discriminate Self from Altered Self and Foreign Nucleic Acids. Immunity. 53(1). 54–77. 110 indexed citations
11.
Coch, Christoph, Thomas Zillinger, Juliane Daßler‐Plenker, et al.. (2019). Human TLR8 Senses RNA From Plasmodium falciparum-Infected Red Blood Cells Which Is Uniquely Required for the IFN-γ Response in NK Cells. Frontiers in Immunology. 10. 371–371. 25 indexed citations
12.
Nischalke, Hans Dieter, Philipp Lutz, Eva Bartok, et al.. (2019). The PNPLA3 I148M variant promotes lipid-induced hepatocyte secretion of CXC chemokines establishing a tumorigenic milieu. Journal of Molecular Medicine. 97(11). 1589–1600. 6 indexed citations
13.
Daßler‐Plenker, Juliane, Annette Paschen, Marion Goldeck, et al.. (2018). Direct RIG‐I activation in human NK cells induces TRAIL‐dependent cytotoxicity toward autologous melanoma cells. International Journal of Cancer. 144(7). 1645–1656. 26 indexed citations
14.
Ludwig‐Portugall, Isis, Eva Bartok, Michael J. Primiano, et al.. (2016). An NLRP3-specific inflammasome inhibitor attenuates crystal-induced kidney fibrosis in mice. Kidney International. 90(3). 525–539. 161 indexed citations
15.
Bartok, Eva, et al.. (2016). Measuring IL-1β Processing by Bioluminescence Sensors II: The iGLuc System. Methods in molecular biology. 1417. 97–113. 7 indexed citations
16.
Schuberth-Wagner, Christine, János Ludwig, Anna‐Maria Herzner, et al.. (2015). A Conserved Histidine in the RNA Sensor RIG-I Controls Immune Tolerance to N1-2′O-Methylated Self RNA. Immunity. 43(1). 41–51. 222 indexed citations
17.
Jakobs, Christopher, et al.. (2013). Immunoblotting for Active Caspase-1. Methods in molecular biology. 1040. 103–115. 51 indexed citations
18.
Bartok, Eva, Franz Bauernfeind, Christopher Jakobs, et al.. (2013). iGLuc: a luciferase-based inflammasome and protease activity reporter. Nature Methods. 10(2). 147–154. 59 indexed citations
19.
Bauernfeind, Franz, et al.. (2011). Cutting Edge: Reactive Oxygen Species Inhibitors Block Priming, but Not Activation, of the NLRP3 Inflammasome. The Journal of Immunology. 187(2). 613–617. 532 indexed citations breakdown →
20.
Bauernfeind, Franz, Andrea Ablasser, Eva Bartok, et al.. (2010). Inflammasomes: current understanding and open questions. Cellular and Molecular Life Sciences. 68(5). 765–783. 301 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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