Judit Kun

1.4k total citations · 1 hit paper
7 papers, 1.0k citations indexed

About

Judit Kun is a scholar working on Molecular Biology, Neurology and Physiology. According to data from OpenAlex, Judit Kun has authored 7 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 2 papers in Neurology and 2 papers in Physiology. Recurrent topics in Judit Kun's work include Protein Structure and Dynamics (3 papers), Alzheimer's disease research and treatments (2 papers) and Neuroinflammation and Neurodegeneration Mechanisms (2 papers). Judit Kun is often cited by papers focused on Protein Structure and Dynamics (3 papers), Alzheimer's disease research and treatments (2 papers) and Neuroinflammation and Neurodegeneration Mechanisms (2 papers). Judit Kun collaborates with scholars based in Hungary, France and Japan. Judit Kun's co-authors include József Kardos, András Micsonai, Éva Bulyáki, Frank Wien, Éva Moussong, Matthieu Réfrégiers, Yuji Goto, Young‐Ho Lee, György Török and Katalin A. Kékesi and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Biophysical Journal.

In The Last Decade

Judit Kun

7 papers receiving 1.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

BeStSel: a web server for accurate protein secondary structure prediction and fold recognition from the circular dichroism spectra

2018 820 citations András Micsonai, Frank Wien et al. Nucleic Acids Research profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Judit Kun Hungary	5	584	149	134	122	109	7	1.0k
Éva Bulyáki Hungary	6	637 1.1×	157 1.1×	125 0.9×	126 1.0×	114 1.0×	8	1.1k
Lai Ding United States	12	1.1k 1.9×	97 0.7×	64 0.5×	172 1.4×	54 0.5×	14	1.4k
Kristoffer Brännström Sweden	23	809 1.4×	382 2.6×	80 0.6×	58 0.5×	79 0.7×	42	1.4k
Mihai Radu Romania	20	486 0.8×	124 0.8×	44 0.3×	52 0.4×	57 0.5×	57	1.2k
Vanessa K. Morris Australia	16	455 0.8×	190 1.3×	48 0.4×	50 0.4×	87 0.8×	27	880
Li Bai China	27	890 1.5×	50 0.3×	63 0.5×	208 1.7×	101 0.9×	75	1.7k
Jing Hong China	23	1.3k 2.3×	219 1.5×	82 0.6×	253 2.1×	57 0.5×	50	1.9k
Rita P.‐Y. Chen Taiwan	21	797 1.4×	299 2.0×	74 0.6×	31 0.3×	133 1.2×	55	1.2k
Giuseppina Pitari Italy	20	716 1.2×	131 0.9×	359 2.7×	134 1.1×	44 0.4×	51	1.5k
Shuiming Li China	22	547 0.9×	169 1.1×	45 0.3×	84 0.7×	367 3.4×	66	1.8k

Countries citing papers authored by Judit Kun

Since Specialization

Citations

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

Fields of papers citing papers by Judit Kun

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Judit Kun

This figure shows the co-authorship network connecting the top 25 collaborators of Judit Kun. A scholar is included among the top collaborators of Judit Kun 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 Judit Kun. Judit Kun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Kardos, József, Éva Moussong, Frank Wien, et al.. (2025). Guide to the structural characterization of protein aggregates and amyloid fibrils by CD spectroscopy. Protein Science. 34(3). e70066–e70066. 11 indexed citations

2.

Vadászi, Henrietta, Éva Bulyáki, György Török, et al.. (2021). Identification of Neuronal Pentraxins as Synaptic Binding Partners of C1q and the Involvement of NP1 in Synaptic Pruning in Adult Mice. Frontiers in Immunology. 11. 599771–599771. 30 indexed citations

3.

Bulyáki, Éva, Judit Kun, Tamás Molnár, et al.. (2021). Pathogenic D76N Variant of β2-Microglobulin: Synergy of Diverse Effects in Both the Native and Amyloid States. Biology. 10(11). 1197–1197. 3 indexed citations

4.

Mark, Kenneth M. K., et al.. (2020). Emergence of prions selectively resistant to combination drug therapy. PLoS Pathogens. 16(5). e1008581–e1008581. 14 indexed citations

5.

Micsonai, András, Frank Wien, Judit Kun, et al.. (2018). Protein Fold Recognition by Circular Dichroism Spectroscopy. Biophysical Journal. 114(3). 174a–174a. 4 indexed citations

6.

Micsonai, András, Frank Wien, Éva Bulyáki, et al.. (2018). BeStSel: a web server for accurate protein secondary structure prediction and fold recognition from the circular dichroism spectra. Nucleic Acids Research. 46(W1). W315–W322. 820 indexed citations breakdown →

7.

Györffy, Balázs A., Judit Kun, György Török, et al.. (2018). Local apoptotic-like mechanisms underlie complement-mediated synaptic pruning. Proceedings of the National Academy of Sciences. 115(24). 6303–6308. 141 indexed citations

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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