Gábor G. Kovács
- Neurology top 0.1%
- Parkinson's Disease Mechanisms and Treatments 99
- Neurological diseases and metabolism 83
- Neurological disorders and treatments 33
- Amyotrophic Lateral Sclerosis Research 25
- Neurology top 0.1%
- Parkinson's Disease Mechanisms and Treatments 99
- Neurological diseases and metabolism 83
- Neurological disorders and treatments 33
- Amyotrophic Lateral Sclerosis Research 25
- Physiology top 0.2%
- Alzheimer's disease research and treatments 115
- Cellular and Molecular Neuroscience top 0.5%
- Neuroscience and Neuropharmacology Research 21
- Developmental Neuroscience top 1%
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- Prion Diseases and Protein Misfolding 78
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- Trace Elements in Health 21
- Co-authors
- Herbert BudkaJasmin RahimiIvan MilenkovićEllen GelpíRomana HöftbergerMirjam I. LutzIsidró FerrerJames W. Ironside
- Cited by
- NeurologyPhysiology
In The Last Decade
Gábor G. Kovács
343 papers receiving 12.5k citations
Hit Papers
Peers
Comparison fields: 5 of 167
- Neurology 3.4k
- Neurology 4.1k
- Physiology 4.7k
- Cellular and Molecular Neuroscience 2.1k
- Developmental Neuroscience 434
Countries citing papers authored by Gábor G. Kovács
This map shows the geographic impact of Gábor G. Kovács'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 Gábor G. Kovács with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gábor G. Kovács more than expected).
Fields of papers citing papers by Gábor G. Kovács
This network shows the impact of papers produced by Gábor G. Kovács. 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 Gábor G. Kovács. The network helps show where Gábor G. Kovács may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Gábor G. Kovács, 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 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 9 | |
| 7 | 2024 | 13 | |
| 8 | 2023 | 10 | |
| 9 | 2023 | 20 | |
| 10 | 2023 | 15 | |
| 11 | 2022 | 5 | |
| 12 | 2022 | 13 | |
| 13 | 2021 | 5 | |
| 14 | 2019 | 14 | |
| 15 | 2019 | 10 | |
| 16 | 2017 | 42 | |
| 17 | 2015 | 26 | |
| 18 | [Human prion diseases: the Hungarian experience]. | 2007 | 2 |
| 19 | MRI mozgu v diagnostike Creutzfeldtovej-Jakobovej choroby | 2007 | 0 |
| 20 | Creutzfeldt-Jakob disease in Hungary. | 2005 | 5 |
About Gábor G. Kovács
Gábor G. Kovács is a scholar working on Neurology, Neurology and Physiology, having authored 362 papers that have together received 12.7k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (115 papers), Parkinson's Disease Mechanisms and Treatments (99 papers), Neurological diseases and metabolism (83 papers), Prion Diseases and Protein Misfolding (78 papers), Neurological disorders and treatments (33 papers), Amyotrophic Lateral Sclerosis Research (25 papers), Trace Elements in Health (21 papers) and Neuroscience and Neuropharmacology Research (21 papers). The work is most often cited by research in Neurology (3.4k citations), Neurology (4.1k citations) and Physiology (4.7k citations). Gábor G. Kovács has collaborated with scholars based in Austria, Hungary and Canada. Frequent co-authors include Herbert Budka, Jasmin Rahimi, Ivan Milenković, Ellen Gelpí, Romana Höftberger, Mirjam I. Lutz, Isidró Ferrer, James W. Ironside, Natallia Makarava and Ilia V. Baskakov. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.
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.