Éva Sághy

685 citations
24 papers · 592 · h-index 14

Impact in

Papers in

Éva Sághy

23 papers receiving 589 citations

Peers

Éva Sághy
Comparison fields: 5 of 81
  • Sensory Systems 234
  • Cellular and Molecular Neuroscience 129
  • Developmental Neuroscience 24
  • Biochemistry 32
  • Physiology 130
Replace Maja Payrits with:
Maja Payrits Hungary
Florian Gackière France
Anna García-Elías Spain
Jean‐Baptiste Roullet United States
Ruirui Lu Germany
Ekaterina Turlova Canada
Alexis G. Bavencoffe United States
Eva Calderón-Sánchez Spain
Monu Goel United States
Hussein N. Rubaiy United Kingdom
Éva Sághy relative to Maja Payrits Hungary Maja Payrits's profile →
Citations per field
00.5×1.7×
Maja Payrits · 1×
Citations per year

Countries citing papers authored by Éva Sághy

Since Specialization
Citations

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

Fields of papers citing papers by Éva Sághy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Éva Sághy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Éva Sághy Line = papers co-authored together Éva Sághy links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201584
2 201555
3 201654
4 201754
5 201845
6 201630
7 201730
8 201629
9 201823
10 201522
11 202021
12 202021
13 202020
14 202117
15 202014
16 202113
17 202112
18 202211
19 202210
20 201510

About Éva Sághy

Éva Sághy is a scholar working on Sensory Systems, Cellular and Molecular Neuroscience, Physiology, Complementary and alternative medicine and Reproductive Medicine, having authored 24 papers that have together received 592 indexed citations. Recurring topics across this work include Ion Channels and Receptors (12 papers), Neuropeptides and Animal Physiology (6 papers), Pain Mechanisms and Treatments (5 papers), Neurobiology and Insect Physiology Research (4 papers), Cardiovascular, Neuropeptides, and Oxidative Stress Research (2 papers), Peptidase Inhibition and Analysis (2 papers), Cardiac Ischemia and Reperfusion (2 papers) and Synthesis and Biological Evaluation (2 papers). The work is most often cited by research in Sensory Systems (234 citations), Cellular and Molecular Neuroscience (129 citations), Developmental Neuroscience (24 citations), Biochemistry (32 citations) and Physiology (130 citations). Éva Sághy has collaborated with scholars based in Hungary, Germany and Poland. Frequent co-authors include Éva Szőke, Zsuzsanna Helyes, Maja Payrits, Janós Szolcsányi, György Sétáló, Krisztina Pohóczky, Erika Pintér, Kata Bölcskei, János Erostyák and Tibor Zoltán Jánosi. Their work appears in journals such as International Journal of Molecular Sciences, Neuroscience, Neuropeptides, Frontiers in Pharmacology and Journal of Neuroimmunology.

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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