Gabriella Fábián
- Molecular Biology
- Cellular and Molecular Neuroscience
- Physiology
- Cancer Research
- Cardiology and Cardiovascular Medicine
- Co-authors
- Mária SzűcsGyöngyi HorváthLászló G. PuskásMargit SzikszayCarmine CosciaEszter MolnárBéla ÓzsváriIván Kanizsai
- Topics
- Neuropeptides and Animal Physiology (8 papers)Receptor Mechanisms and Signaling (6 papers)Pharmacological Receptor Mechanisms and Effects (3 papers)
In The Last Decade
Gabriella Fábián
21 papers receiving 338 citations
Peers
Comparison fields: 5 of 76
- Molecular Biology 197
- Cellular and Molecular Neuroscience 111
- Physiology 60
- Cancer Research 34
- Cardiology and Cardiovascular Medicine 32
Countries citing papers authored by Gabriella Fábián
This map shows the geographic impact of Gabriella Fábián'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 Gabriella Fábián with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabriella Fábián more than expected).
Fields of papers citing papers by Gabriella Fábián
This network shows the impact of papers produced by Gabriella Fábián. 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 Gabriella Fábián. The network helps show where Gabriella Fábián may publish in the future.
Co-authorship network of co-authors of Gabriella Fábián
This figure shows the co-authorship network connecting the top 25 collaborators of Gabriella Fábián. A scholar is included among the top collaborators of Gabriella Fábián 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 Gabriella Fábián. Gabriella Fábián is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 24 | |
| 3 | High-dose Radiation Induced Heart Damage in a Rat Model. | 25 |
| 4 | 6 | |
| 5 | 51 | |
| 6 | 9 | |
| 7 | 1 | |
| 8 | 10 | |
| 9 | 7 | |
| 10 | 9 | |
| 11 | Removal of nonspecific binding proteins from cell and tissue extracts using 2-aminobenzimidazole-tethered affinity resin. | 2 |
| 12 | 12 | |
| 13 | 41 | |
| 14 | 42 | |
| 15 | 9 | |
| 16 | 53 | |
| 17 | Heterotrimeric G-proteins and their role in opioid receptor function | 1 |
| 18 | 6 | |
| 19 | 27 | |
| 20 | 3 |
About Gabriella Fábián
Gabriella Fábián is a scholar working on Cellular and Molecular Neuroscience, Biochemistry and Molecular Biology, having authored 21 papers that have together received 347 indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (8 papers), Receptor Mechanisms and Signaling (6 papers) and Pharmacological Receptor Mechanisms and Effects (3 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (111 citations), Molecular Medicine (30 citations) and Biochemistry (23 citations). Gabriella Fábián has collaborated with scholars based in Hungary, Germany and Austria. Frequent co-authors include Mária Szűcs, Gyöngyi Horváth, László G. Puskás, Margit Szikszay, Carmine Coscia, Eszter Molnár, Béla Ózsvári, Iván Kanizsai, Nóra Faragó and Zoltán Varga. Their work appears in journals such as PLoS ONE, International Journal of Molecular Sciences and Journal of Medicinal Chemistry.
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.