Éva Varga

2.5k total citations
82 papers, 2.0k citations indexed

About

Éva Varga is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Physiology. According to data from OpenAlex, Éva Varga has authored 82 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Molecular Biology, 65 papers in Cellular and Molecular Neuroscience and 15 papers in Physiology. Recurrent topics in Éva Varga's work include Neuropeptides and Animal Physiology (58 papers), Receptor Mechanisms and Signaling (52 papers) and Pharmacological Receptor Mechanisms and Effects (29 papers). Éva Varga is often cited by papers focused on Neuropeptides and Animal Physiology (58 papers), Receptor Mechanisms and Signaling (52 papers) and Pharmacological Receptor Mechanisms and Effects (29 papers). Éva Varga collaborates with scholars based in United States, Hungary and Japan. Éva Varga's co-authors include Henry I. Yamamura, William R. Roeske, Victor J. Hruby, Dagmar Stropova, Scott Cowell, Zdzislaw Salamon, Gordon Tollin, Todd W. Vanderah, Thomas H. Burkey and Yoshiaki Hosohata and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Éva Varga

81 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Éva Varga United States 27 1.4k 1.2k 362 181 84 82 2.0k
Gregory A. Weiland United States 22 1.6k 1.1× 950 0.8× 163 0.5× 117 0.6× 58 0.7× 39 1.9k
Michele Chiesi Switzerland 32 2.2k 1.5× 564 0.5× 670 1.9× 106 0.6× 48 0.6× 66 3.3k
Arthur J. Blume United States 30 2.0k 1.4× 1.2k 1.0× 584 1.6× 250 1.4× 136 1.6× 58 2.9k
Shoji Maeda Japan 24 2.4k 1.7× 1.0k 0.8× 140 0.4× 193 1.1× 92 1.1× 45 2.9k
Michel Fink France 24 4.7k 3.3× 2.5k 2.1× 415 1.1× 125 0.7× 62 0.7× 27 5.5k
Linghui Zeng China 28 1.3k 0.9× 785 0.7× 460 1.3× 111 0.6× 261 3.1× 103 2.7k
Eliezer Giladi Israel 26 981 0.7× 913 0.8× 472 1.3× 180 1.0× 226 2.7× 44 2.2k
Joseph Goldfarb United States 27 1.2k 0.8× 1.1k 0.9× 419 1.2× 224 1.2× 49 0.6× 57 2.5k
Jelveh Lameh United States 24 1.6k 1.1× 1.3k 1.1× 246 0.7× 105 0.6× 71 0.8× 53 2.2k
Ada De Luigi Italy 27 1.2k 0.8× 939 0.8× 631 1.7× 199 1.1× 175 2.1× 54 3.2k

Countries citing papers authored by Éva Varga

Since Specialization
Citations

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

Fields of papers citing papers by Éva Varga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Éva Varga

This figure shows the co-authorship network connecting the top 25 collaborators of Éva Varga. A scholar is included among the top collaborators of Éva Varga 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 Éva Varga. Éva Varga 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.
Krausz, Sarah, Éva Varga, Krisztina Huszár, et al.. (2025). ProPE expands the prime editing window and enhances gene editing efficiency where prime editing is inefficient. Nature Catalysis. 8(10). 1100–1116.
2.
Skurzak, H, Sergiusz Markowicz, Anna Leśniak, et al.. (2013). Original article Opioid agonist – tachykinin antagonist as a new analgesic with adjuvant anticancer properties. Folia Neuropathologica. 2(2). 132–139. 11 indexed citations
3.
Guillemyn, Karel, Attila Keresztes, Éva Varga, et al.. (2012). Solid phase synthesis and biological evaluation of novel bifunctional opioid agonist - neurokinin-1 antagonist peptidomimetics: IF 2.07. Journal of Peptide Science. 18. 123–124. 1 indexed citations
4.
Vardanyan, Ruben, Vlad K. Kumirov, Gary S. Nichol, et al.. (2011). Synthesis and biological evaluation of new opioid agonist and neurokinin-1 antagonist bivalent ligands. Bioorganic & Medicinal Chemistry. 19(20). 6135–6142. 22 indexed citations
5.
Varga, Éva, Teodora Georgieva, Suneeta Tumati, et al.. (2008). Functional Selectivity in Cannabinoid Signaling. Current Molecular Pharmacology. 1(3). 273–284. 13 indexed citations
6.
Tumati, Suneeta, Edita Navratilova, Paul A. St. John, et al.. (2008). Sustained morphine treatment augments basal CGRP release from cultured primary sensory neurons in a Raf-1 dependent manner. European Journal of Pharmacology. 584(2-3). 272–277. 28 indexed citations
7.
Navratilova, Edita, Sue Waite, Dagmar Stropova, et al.. (2007). Quantitative Evaluation of Human δ Opioid Receptor Desensitization Using the Operational Model of Drug Action. Molecular Pharmacology. 71(5). 1416–1426. 15 indexed citations
8.
Hruby, Victor J., Frank Porreca, Henry I. Yamamura, et al.. (2006). New paradigms and tools in drug design for pain and addiction. The AAPS Journal. 8(3). E450–E460. 21 indexed citations
9.
Varga, Éva, et al.. (2004). Agonist-specific regulation of the δ-opioid receptor. Life Sciences. 76(6). 599–612. 34 indexed citations
10.
Varga, Éva. (2003). The molecular mechanisms of cellular tolerance to δ-opioid agonists. Acta Biologica Hungarica. 54(2). 203–218. 5 indexed citations
11.
Varga, Éva, Dagmar Stropova, Victor J. Hruby, et al.. (2003). Converging Protein Kinase Pathways Mediate Adenylyl Cyclase Superactivation upon Chronic δ-Opioid Agonist Treatment. Journal of Pharmacology and Experimental Therapeutics. 306(1). 109–115. 41 indexed citations
12.
Varga, Éva, et al.. (2002). Involvement of Raf-1 in chronic δ-opioid receptor agonist-mediated adenylyl cyclase superactivation. European Journal of Pharmacology. 451(1). 101–102. 41 indexed citations
13.
Salamon, Zdzislaw, Scott Cowell, Éva Varga, et al.. (2000). Plasmon Resonance Studies of Agonist/Antagonist Binding to theHuman δ-Opioid Receptor: New Structural Insights into Receptor-Ligand Interactions. Biophysical Journal. 79(5). 2463–2474. 87 indexed citations
14.
Hosohata, Keiko, Jennifer Logan, Éva Varga, et al.. (2000). The role of the G protein γ2 subunit in opioid antinociception in mice. European Journal of Pharmacology. 392(3). R9–R11. 14 indexed citations
15.
Varga, Éva, Dagmar Stropova, Man Wang, et al.. (1998). Identification of adenylyl cyclase isoenzymes in CHO and B82 cells. European Journal of Pharmacology. 348(2-3). R1–R2. 46 indexed citations
16.
Burkey, Thomas H., Frederick J. Ehlert, Yoshiaki Hosohata, et al.. (1998). The efficacy of δ-opioid receptor-selective drugs. Life Sciences. 62(17-18). 1531–1536. 13 indexed citations
17.
Knapp, Richard J., Ewa Malatyńska, Lei Fang, et al.. (1994). Identification of a human delta opioid receptor: Cloning and expression. Life Sciences. 54(25). PL463–PL469. 105 indexed citations
18.
19.
Simon, Joseph, Sándor Benyhe, Éva Varga, et al.. (1990). Method for isolation of kappa‐opioid binding sites by dynorphin affinity chromatography. Journal of Neuroscience Research. 25(4). 549–555. 17 indexed citations
20.
Simon, Joseph, et al.. (1988). Characterization of human placental opioid receptors by 3H-ethylketocyclazocine and 3H-naloxone binding. Neuropeptides. 12(3). 171–176. 5 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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