F. Deák

10.0k citations
131 papers · 5.3k · 1 hit paper · h-index 35

Impact in

Papers in

F. Deák

128 papers receiving 5.2k citations

F. Deák's Hit Papers

SNARE Function Analyzed in Synaptobrevin/VAMP Knockout Mice 2001 · 503 citations
5030+8+16Years since publication100200300400500

Peers

F. Deák
Comparison fields: 5 of 145
  • Cell Biology 1.5k
  • Immunology and Allergy 407
  • Cellular and Molecular Neuroscience 1.2k
  • Neurology 452
  • Nuclear and High Energy Physics 656
Replace P. Sonderegger with:
P. Sonderegger Switzerland
Roland Schüle Germany
M. Kœnig France
Kazuhiko Kume Japan
Markus Morawski Germany
P. G. Barth Netherlands
Markus Rudin Switzerland
Russell E. Jacobs United States
Scott R. VandenBerg United States
Mark F. Lythgoe United Kingdom
F. Deák relative to P. Sonderegger Switzerland P. Sonderegger's profile →
Citations per field
00.5×1.5×2.4×
P. Sonderegger · 1×
Citations per year

Countries citing papers authored by F. Deák

Since Specialization
Citations

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

Fields of papers citing papers by F. Deák

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 131 papers — load more, or switch the sort, to bring in the rest.

#Work
1
SNARE Function Analyzed in Synaptobrevin/VAMP Knockout Mice
Hit paper breakdown →
2001503
2 2005309
3 2004202
4 2013194
5 2014163
6 1993141
7 1993140
8 2017136
9 1999132
10 2013131
11 2009130
12 2012127
13 2006119
14 2015119
15 2000114
16 2013114
17 2007101
18 200692
19 198991
20 198786

About F. Deák

F. Deák is a scholar working on Molecular Biology, Nuclear and High Energy Physics, Radiation, Cell Biology and Cellular and Molecular Neuroscience, having authored 131 papers that have together received 5.3k indexed citations. Recurring topics across this work include Nuclear physics research studies (37 papers), Nuclear Physics and Applications (26 papers), Cell Adhesion Molecules Research (15 papers), Cellular transport and secretion (14 papers), Astronomical and nuclear sciences (13 papers), Nuclear reactor physics and engineering (13 papers), Osteoarthritis Treatment and Mechanisms (13 papers) and Neuroscience and Neuropharmacology Research (12 papers). The work is most often cited by research in Cell Biology (1.5k citations), Immunology and Allergy (407 citations), Cellular and Molecular Neuroscience (1.2k citations), Neurology (452 citations) and Nuclear and High Energy Physics (656 citations). F. Deák has collaborated with scholars based in Hungary, United States and Japan. Frequent co-authors include Ege T. Kavalali, Thomas C. Südhof, William E. Sonntag, Xinran Liu, Yıldırım Sara, Ibolya Kiss, Susanne Schoch, Anna Csiszár, Zoltán Ungvári and Andreas Königstorfer. Their work appears in journals such as Matrix Biology, The Journals of Gerontology Series A, GeroScience, Nuclear Physics A and Journal of Biological 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.

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