György Váró

4.4k total citations
97 papers, 3.7k citations indexed

About

György Váró is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Biomedical Engineering. According to data from OpenAlex, György Váró has authored 97 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Cellular and Molecular Neuroscience, 47 papers in Molecular Biology and 24 papers in Biomedical Engineering. Recurrent topics in György Váró's work include Photoreceptor and optogenetics research (69 papers), Neuroscience and Neuropharmacology Research (41 papers) and Molecular Communication and Nanonetworks (20 papers). György Váró is often cited by papers focused on Photoreceptor and optogenetics research (69 papers), Neuroscience and Neuropharmacology Research (41 papers) and Molecular Communication and Nanonetworks (20 papers). György Váró collaborates with scholars based in Hungary, United States and Romania. György Váró's co-authors include Janos Κ. Lanyi, Richard Needleman, Janos K. Lanyi, L. Keszthelyi, Csilla Gergely, László Zimányi, Baofu Ni, Man Chang, Yi Cao and Constanţa Ganea and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Lancet and Journal of Biological Chemistry.

In The Last Decade

György Váró

96 papers receiving 3.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
György Váró Hungary 34 3.0k 1.9k 518 504 400 97 3.7k
Hans-Thomas Richter United States 10 2.2k 0.7× 1.9k 1.0× 174 0.3× 385 0.8× 171 0.4× 10 2.8k
Yuki Sudo Japan 33 2.5k 0.8× 1.8k 0.9× 384 0.7× 177 0.4× 310 0.8× 150 3.1k
Kiryl D. Piatkevich United States 28 1.2k 0.4× 1.8k 1.0× 560 1.1× 113 0.2× 316 0.8× 73 3.4k
Jonathan S. Marvin United States 26 1.3k 0.5× 2.0k 1.1× 260 0.5× 127 0.3× 476 1.2× 44 3.4k
Jean‐Philippe Cartailler United States 17 1.7k 0.6× 1.8k 0.9× 149 0.3× 264 0.5× 143 0.4× 40 2.6k
Thomas E. Hughes United States 26 1.3k 0.4× 1.7k 0.9× 464 0.9× 69 0.1× 192 0.5× 64 3.1k
Satoshi P. Tsunoda Japan 28 2.2k 0.7× 1.6k 0.8× 598 1.2× 92 0.2× 483 1.2× 52 3.1k
Christian G. Specht France 28 1.3k 0.4× 1.7k 0.9× 171 0.3× 261 0.5× 206 0.5× 45 3.0k
Joseph P. Wuskell United States 22 789 0.3× 913 0.5× 209 0.4× 88 0.2× 243 0.6× 29 2.0k
Mikihiro Shibata Japan 25 791 0.3× 957 0.5× 238 0.5× 96 0.2× 100 0.3× 58 1.9k

Countries citing papers authored by György Váró

Since Specialization
Citations

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

Fields of papers citing papers by György Váró

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of György Váró

This figure shows the co-authorship network connecting the top 25 collaborators of György Váró. A scholar is included among the top collaborators of György Váró 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 György Váró. György Váró 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
1.
Nagy, Krisztina, Balázs Bogos, Zsolt Szegletes, et al.. (2016). Antimicrobial nodule-specific cysteine-rich peptides disturb the integrity of bacterial outer and inner membranes and cause loss of membrane potential. Annals of Clinical Microbiology and Antimicrobials. 15(1). 43–43. 40 indexed citations
2.
Bovino, Fabio Antonio, Maria Cristina Larciprete, C. Sibilia, György Váró, & Csilla Gergely. (2012). Evidence of multipolar response of Bacteriorhodopsin by noncollinear second harmonic generation. Optics Express. 20(13). 14621–14621. 5 indexed citations
3.
Végh, Attila G., Krisztina Nagy, Zoltán Bálint, et al.. (2011). Effect of Antimicrobial Peptide‐Amide: Indolicidin on Biological Membranes. BioMed Research International. 2011(1). 670589–670589. 19 indexed citations
4.
Végh, Attila G., Csilla Fazakas, Krisztina Nagy, et al.. (2011). Spatial and temporal dependence of the cerebral endothelial cells elasticity. Journal of Molecular Recognition. 24(3). 422–428. 13 indexed citations
5.
Bhattacharya, P., et al.. (2007). Low-power bacteriorhodopsin-silicon n-channel metal-oxide field-effect transistor photoreceiver. Optics Letters. 32(5). 500–500. 10 indexed citations
6.
Bhattacharya, P., et al.. (2004). Monolithically integrated bacteriorhodopsin–GaAs/GaAlAs phototransceiver. Optics Letters. 29(19). 2264–2264. 9 indexed citations
7.
Xu, Jianbin, P. Bhattacharya, & György Váró. (2003). Photo-induced anisotropic photoelectric response in oriented bacteriorhodopsin films. Optical Materials. 22(4). 321–326. 3 indexed citations
8.
Lanyi, Janos Κ., et al.. (2003). The Photochemical Reaction Cycle of Proteorhodopsin at Low pH. Biophysical Journal. 84(5). 3252–3256. 55 indexed citations
9.
Groma, Géza I., et al.. (2002). Characterization of the Azide-Dependent Bacteriorhodopsin-Like Photocycle of Salinarum Halorhodopsin. Biophysical Journal. 82(4). 1687–1695. 9 indexed citations
10.
Groma, Géza I., et al.. (2001). Photocycle of Dried Acid Purple Form of Bacteriorhodopsin. Biophysical Journal. 81(6). 3432–3441. 13 indexed citations
11.
Gergely, Csilla, László Zimányi, & György Váró. (1997). Bacteriorhodopsin Intermediate Spectra Determined over a Wide pH Range. The Journal of Physical Chemistry B. 101(45). 9390–9395. 68 indexed citations
12.
Váró, György, László Zimányi, Xiaoning Fan, et al.. (1995). Photocycle of halorhodopsin from Halobacterium salinarium. Biophysical Journal. 68(5). 2062–2072. 85 indexed citations
13.
Váró, György, Leonid S. Brown, Jun Sasaki, et al.. (1995). Light-Driven Chloride Ion Transport by Halorhodopsin from Natronobacterium pharaonis. I. The Photochemical Cycle. Biochemistry. 34(44). 14490–14499. 88 indexed citations
14.
Gergely, Csilla, Constanţa Ganea, Géza I. Groma, & György Váró. (1993). Study of the photocycle and charge motions of the bacteriorhodopsin mutant D96N. Biophysical Journal. 65(6). 2478–2483. 36 indexed citations
15.
Váró, György, László Zimányi, Mi Chang, et al.. (1992). A residue substitution near the beta-ionone ring of the retinal affects the M substates of bacteriorhodopsin. Biophysical Journal. 61(3). 820–826. 25 indexed citations
16.
Dioumaev, Andrei K., et al.. (1992). Kinetics of the fast electric signal from oriented purple membrane. Biophysical Journal. 61(5). 1194–1200. 5 indexed citations
17.
Zimányi, László, György Váró, Man Chang, et al.. (1992). Pathways of proton release in the bacteriorhodopsin photocycle. Biochemistry. 31(36). 8535–8543. 183 indexed citations
18.
19.
Váró, György, et al.. (1991). The photocycle of bacteriorhodopsin immobilized in poly(vinyl alcohol) film. FEBS Letters. 285(1). 66–70. 11 indexed citations
20.
Váró, György, Albert Duschl, & Janos K. Lanyi. (1990). Interconversions of the M, N, and O intermediates in the bacteriorhodopsin photocycle. Biochemistry. 29(15). 3798–3804. 35 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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