Kinga Nagy

589 citations
32 papers · 361 · h-index 10

Impact in

  • Equine top 2%
    • Veterinary Equine Medical Research
    • Animal Behavior and Welfare Studies

Papers in

    • Glycosylation and Glycoproteins Research 2
    • Advanced Proteomics Techniques and Applications 5
    • Mass Spectrometry Techniques and Applications 4

Kinga Nagy

28 papers receiving 359 citations

Peers

Kinga Nagy
Comparison fields: 5 of 88
  • Equine 58
  • Small Animals 61
  • Animal Science and Zoology 68
  • Rehabilitation 33
  • Agronomy and Crop Science 27
Replace Laura Da Dalt with:
Laura Da Dalt Italy
Ewa Jastrzębska Poland
D.A. van Doorn Netherlands
Susan D. Lauten United States
Liang Deng China
K. Słoniewski Poland
Byung-Wook Cho South Korea
Elizabeth A. Staiger United States
M. C. Pereira Brazil
D. D. Burnett United States
Kinga Nagy relative to Laura Da Dalt Italy Laura Da Dalt's profile →
Citations per field
00.5×4.7×
Laura Da Dalt · 1×
Citations per year

Countries citing papers authored by Kinga Nagy

Since Specialization
Citations

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

Fields of papers citing papers by Kinga Nagy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Kinga Nagy, 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 Kinga Nagy Line = papers co-authored together Kinga Nagy links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201384
2 201766
3 201938
4 201526
5 201824
6 202418
7 202017
8 201412
9 201910
10 202210
11 20236
12 20145
13 20165
14 20225
15 20105
16 20104
17 20244
18 20233
19 20223
20 20213

About Kinga Nagy

Kinga Nagy is a scholar working on Molecular Biology, Spectroscopy, Nutrition and Dietetics, Small Animals and Social Psychology, having authored 32 papers that have together received 361 indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (5 papers), Mass Spectrometry Techniques and Applications (4 papers), Point processes and geometric inequalities (2 papers), Glycosylation and Glycoproteins Research (2 papers), Selenium in Biological Systems (2 papers), Microplastics and Plastic Pollution (2 papers), Animal Behavior and Welfare Studies (2 papers) and Veterinary Equine Medical Research (2 papers). The work is most often cited by research in Equine (58 citations), Small Animals (61 citations), Animal Science and Zoology (68 citations), Rehabilitation (33 citations) and Agronomy and Crop Science (27 citations). Kinga Nagy has collaborated with scholars based in Hungary, United Kingdom and Italy. Frequent co-authors include O. Szenci, Beáta G. Vértessy, Jean‐François Beckers, Noelita Melo de Sousa, Orsolya Kutasi, Péter Póti, Fruzsina Luca Kézér, Levente Kovács, Ágnes Révész and Vince Grolmusz. Their work appears in journals such as Journal of the American Society for Mass Spectrometry, JNCI Journal of the National Cancer Institute, Journal of Proteome Research, PLoS ONE and Scientific Reports.

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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