András Zeke

2.2k citations
25 papers · 1.2k indexed · 1 hit paper · h-index 13
Topics
RNA and protein synthesis mechanisms (7 papers)Protein Structure and Dynamics (5 papers)Machine Learning in Bioinformatics (4 papers)

In The Last Decade

András Zeke

24 papers receiving 1.2k citations

Hit Papers

JNK Signaling: Regulation and Functions Based on Complex ...20162026201920222016100200300

Peers

András Zeke
Comparison fields: 5 of 105
  • Molecular Biology 906
  • Cell Biology 148
  • Oncology 120
  • Immunology 111
  • Computational Theory and Mathematics 87
Replace Jessica K. Gagnon with:
Jessica K. Gagnon United States
Farrell MacKenzie Canada
Ghita Ghislat United Kingdom
Paul M. Steed United States
Rana Anjum India
Qixu Cai China
Mathieu Lavallée‐Adam Canada
Fuxiao Xin United States
Heming Xing United States
Peter Thul Germany
András Zeke relative to Jessica K. Gagnon United States Jessica K. Gagnon's profile →
Citations per field
00.5×1.5×
Jessica K. Gagnon · 1×
Citations per year

Countries citing papers authored by András Zeke

Since Specialization
Citations

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

Fields of papers citing papers by András Zeke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of András Zeke

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 0
3 2
4 1
5 11
6 25
7 6
8 44
9 8
10 153
11 38
12 35
13 39
14 9
15 38
16 10
17 25
18 48
19 133
20 116

About András Zeke

András Zeke is a scholar working on Molecular Biology, Cell Biology and Biophysics, having authored 25 papers that have together received 1.2k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (7 papers), Protein Structure and Dynamics (5 papers) and Machine Learning in Bioinformatics (4 papers). The work is most often cited by research in Molecular Biology (906 citations), Cell Biology (148 citations) and Aging (11 citations). András Zeke has collaborated with scholars based in Hungary, Germany and United States. Frequent co-authors include Attila Reményi, Mariya Misheva, Marie A. Bogoyevitch, Wendell A. Lim, Bálint Mészáros, Anita Alexa, László Dobson, Zsuzsanna Dosztányi, Gergő Gógl and János Varga. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research 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.

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