Katalin Bánki
- Immunology top 2%
- T-cell and Retrovirus Studies 6
- Neutrophil, Myeloperoxidase and Oxidative Mechanisms 4
- Rheumatology top 1%
- Systemic Lupus Erythematosus Research 10
- Biochemistry top 2%
- Amino Acid Enzymes and Metabolism 9
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- Biomedical Research and Pathophysiology 20
- Virology top 5%
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- Neonatal Health and Biochemistry 9
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- Porphyrin Metabolism and Disorders 5
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- Monoclonal and Polyclonal Antibodies Research 4
- Co-authors
- András PerlP GergelyNick J. GonchoroffEliza HutterFerenc PuskásPaul E. M. PhillipsBrian NilandZachary Oaks
- Cited by
- ImmunologyRheumatologyBiochemistry
- Journals
- Proceedings of the National Academy of Sciences (2 papers)Journal of Biological Chemistry (6 papers)Journal of Clinical Investigation (2 papers)
- Partner nations
- United StatesRussiaItaly
In The Last Decade
Katalin Bánki
50 papers receiving 2.9k citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Immunology 1.2k
- Rheumatology 696
- Biochemistry 229
- Pathology and Forensic Medicine 503
- Virology 94
Countries citing papers authored by Katalin Bánki
This map shows the geographic impact of Katalin Bánki'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 Katalin Bánki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Katalin Bánki more than expected).
Fields of papers citing papers by Katalin Bánki
This network shows the impact of papers produced by Katalin Bánki. 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 Katalin Bánki. The network helps show where Katalin Bánki may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Katalin Bánki, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Rab4A-directed endosome traffic shapes pro-inflammatory mitochondrial metabolism in T cells via mitophagy, CD98 expression, and kynurenine-sensitive mTOR activationbreakdown → | 2024 | 52 |
| 2 | 2023 | 24 | |
| 3 | 2023 | 30 | |
| 4 | 2021 | 6 | |
| 5 | 2019 | 16 | |
| 6 | 2018 | 12 | |
| 7 | 2014 | 40 | |
| 8 | 2013 | 144 | |
| 9 | 2010 | 20 | |
| 10 | 2006 | 20 | |
| 11 | 2005 | 29 | |
| 12 | 2004 | 28 | |
| 13 | 2004 | 191 | |
| 14 | 1999 | 48 | |
| 15 | 1999 | 240 | |
| 16 | 1997 | 63 | |
| 17 | 1996 | 25 | |
| 18 | 1995 | 78 | |
| 19 | 1994 | 3 | |
| 20 | 1994 | 119 |
About Katalin Bánki
Katalin Bánki is a scholar working on Biochemistry, Pathology and Forensic Medicine and Immunology, having authored 50 papers that have together received 2.9k indexed citations. Recurring topics across this work include Biomedical Research and Pathophysiology (20 papers), Systemic Lupus Erythematosus Research (10 papers), Amino Acid Enzymes and Metabolism (9 papers), Neonatal Health and Biochemistry (9 papers), T-cell and Retrovirus Studies (6 papers), Porphyrin Metabolism and Disorders (5 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (4 papers) and Monoclonal and Polyclonal Antibodies Research (4 papers). The work is most often cited by research in Immunology (1.2k citations), Rheumatology (696 citations) and Biochemistry (229 citations). Katalin Bánki has collaborated with scholars based in United States, Russia and Italy. Frequent co-authors include András Perl, P Gergely, Nick J. Gonchoroff, Eliza Hutter, Ferenc Puskás, Paul E. M. Phillips, Brian Niland, Zachary Oaks, Craig E. Grossman and György Nagy. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Investigation.
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.