Vanja Nagy

3.5k total citations · 1 hit paper
23 papers, 2.7k citations indexed

About

Vanja Nagy is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Genetics. According to data from OpenAlex, Vanja Nagy has authored 23 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 9 papers in Cellular and Molecular Neuroscience and 6 papers in Genetics. Recurrent topics in Vanja Nagy's work include Neuropeptides and Animal Physiology (4 papers), Pain Mechanisms and Treatments (3 papers) and Axon Guidance and Neuronal Signaling (3 papers). Vanja Nagy is often cited by papers focused on Neuropeptides and Animal Physiology (4 papers), Pain Mechanisms and Treatments (3 papers) and Axon Guidance and Neuronal Signaling (3 papers). Vanja Nagy collaborates with scholars based in Austria, United States and Australia. Vanja Nagy's co-authors include Ivone Gomes, Nino Trapaidze, Ankur Gupta, Lakshmi A. Devi, Bryen A. Jordan, George W. Huntley, Ozlem Bozdagi, Josef Penninger, Sam Gandy and Suzana Petanceska and has published in prestigious journals such as Nature, Nature Communications and Journal of Neuroscience.

In The Last Decade

Vanja Nagy

23 papers receiving 2.6k citations

Hit Papers

SHARPIN forms a linear ubiquitin ligase complex regulatin... 2011 2026 2016 2021 2011 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vanja Nagy Austria 14 1.6k 1.1k 471 454 337 23 2.7k
Marı́a Santacana Spain 34 1.3k 0.8× 870 0.8× 469 1.0× 273 0.6× 244 0.7× 111 3.2k
Emilio Casanova Austria 29 2.2k 1.3× 1.3k 1.2× 244 0.5× 369 0.8× 494 1.5× 86 4.3k
Michael D. Conkright United States 15 2.2k 1.3× 553 0.5× 462 1.0× 379 0.8× 234 0.7× 21 3.2k
Laura Sanders United States 13 1.8k 1.1× 799 0.7× 246 0.5× 505 1.1× 450 1.3× 14 3.2k
Andrea Levi Italy 30 1.4k 0.8× 1.1k 1.1× 211 0.4× 470 1.0× 179 0.5× 60 2.7k
Raya Eilam Israel 40 1.7k 1.0× 718 0.7× 506 1.1× 547 1.2× 648 1.9× 70 4.3k
Jean‐Christophe Deloulme France 31 2.6k 1.6× 1.4k 1.3× 356 0.8× 372 0.8× 347 1.0× 64 4.1k
Mark H. G. Verheijen Netherlands 25 2.4k 1.5× 930 0.9× 188 0.4× 541 1.2× 381 1.1× 52 3.9k
Séan Wyatt United Kingdom 26 1.3k 0.8× 1.5k 1.4× 222 0.5× 383 0.8× 262 0.8× 70 2.8k
Donald Pizzo United States 31 1.7k 1.0× 643 0.6× 577 1.2× 451 1.0× 267 0.8× 80 3.1k

Countries citing papers authored by Vanja Nagy

Since Specialization
Citations

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

Fields of papers citing papers by Vanja Nagy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vanja Nagy

This figure shows the co-authorship network connecting the top 25 collaborators of Vanja Nagy. A scholar is included among the top collaborators of Vanja Nagy 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 Vanja Nagy. Vanja Nagy 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.
Langeslag, Michiel, Cosmin I. Ciotu, Michael J. M. Fischer, et al.. (2022). Transcription factor mesenchyme homeobox protein 2 (MEOX2) modulates nociceptor function. FEBS Journal. 289(12). 3457–3476. 4 indexed citations
2.
Vulliard, Loan, Joana Ferreira da Silva, Joanna I. Loizou, et al.. (2021). BioProfiling.jl: profiling biological perturbations with high-content imaging in single cells and heterogeneous populations. Bioinformatics. 38(6). 1692–1699. 5 indexed citations
3.
Nagy, Vanja, et al.. (2021). Expanding the known phenotype of Mullegama–Klein–Martinez syndrome in male patients. Human Genome Variation. 8(1). 37–37. 4 indexed citations
4.
Nagy, Vanja, et al.. (2021). Network analysis reveals rare disease signatures across multiple levels of biological organization. Nature Communications. 12(1). 6306–6306. 47 indexed citations
5.
Nagy, Vanja, et al.. (2021). Cellular Models and High-Throughput Screening for Genetic Causality of Intellectual Disability. Trends in Molecular Medicine. 27(3). 220–230. 9 indexed citations
6.
Alehabib, Elham, Sakineh Ranji‐Burachaloo, Abbas Tafakhori, et al.. (2021). Leu226Trp CACNA1A variant associated with juvenile myoclonic epilepsy with and without intellectual disability. Clinical Neurology and Neurosurgery. 213. 107108–107108. 4 indexed citations
7.
Langeslag, Michiel, John Manion, Elham Alehabib, et al.. (2021). PRDM12 Is Transcriptionally Active and Required for Nociceptor Function Throughout Life. Frontiers in Molecular Neuroscience. 14. 720973–720973. 8 indexed citations
8.
Nagy, Vanja, et al.. (2020). PRDM12: New Opportunity in Pain Research. Trends in Molecular Medicine. 26(10). 895–897. 10 indexed citations
9.
Vermeiren, Simon, Claude Van Campenhout, Sadia Kricha, et al.. (2019). Prdm12 Directs Nociceptive Sensory Neuron Development by Regulating the Expression of the NGF Receptor TrkA. Cell Reports. 26(13). 3522–3536.e5. 40 indexed citations
10.
Lee, Nicola J., et al.. (2018). Central RANK signalling in NPY neurons alters bone mass in male mice. Neuropeptides. 68. 75–83. 7 indexed citations
11.
Nagy, Vanja & Josef Penninger. (2015). The RANKL-RANK Story. Gerontology. 61(6). 534–542. 132 indexed citations
12.
Ikeda, Fumiyo, Yonathan Lissanu Deribe, Sigrid S. Skånland, et al.. (2011). SHARPIN forms a linear ubiquitin ligase complex regulating NF-κB activity and apoptosis. Nature. 471(7340). 637–641. 574 indexed citations breakdown →
13.
Nagy, Vanja & Ivan Đikić. (2009). Ubiquitin ligase complexes: from substrate selectivity to conjugational specificity. Biological Chemistry. 391(2-3). 163–169. 75 indexed citations
14.
15.
Bozdagi, Ozlem, et al.. (2007). In Vivo Roles for Matrix Metalloproteinase-9 in Mature Hippocampal Synaptic Physiology and Plasticity. Journal of Neurophysiology. 98(1). 334–344. 155 indexed citations
16.
Nagy, Vanja, Ozlem Bozdagi, & George W. Huntley. (2007). The extracellular protease matrix metalloproteinase-9 is activated by inhibitory avoidance learning and required for long-term memory. Learning & Memory. 14(10). 655–664. 86 indexed citations
17.
Nagy, Vanja, Ozlem Bozdagi, Anna Matynia, et al.. (2006). Matrix Metalloproteinase-9 Is Required for Hippocampal Late-Phase Long-Term Potentiation and Memory. Journal of Neuroscience. 26(7). 1923–1934. 413 indexed citations
18.
Petanceska, Suzana, Vanja Nagy, D E Frail, & Sam Gandy. (2000). Ovariectomy and 17β-estradiol modulate the levels of Alzheimer's amyloid β peptides in brain. Experimental Gerontology. 35(9-10). 1317–1325. 97 indexed citations
19.
Gomes, Ivone, Bryen A. Jordan, Ankur Gupta, et al.. (2000). Heterodimerization of μ and δ Opioid Receptors: A Role in Opiate Synergy. Journal of Neuroscience. 20(22). RC110–RC110. 347 indexed citations
20.
Gomes, Ivone, Bryen A. Jordan, Ankur Gupta, et al.. (2000). Heterodimerization of mu and delta opioid receptors: A role in opiate synergy.. PubMed. 20(22). RC110–RC110. 386 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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