Fabio Vilardi

725 total citations
11 papers, 496 citations indexed

About

Fabio Vilardi is a scholar working on Molecular Biology, Cell Biology and Epidemiology. According to data from OpenAlex, Fabio Vilardi has authored 11 papers receiving a total of 496 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 6 papers in Cell Biology and 2 papers in Epidemiology. Recurrent topics in Fabio Vilardi's work include Endoplasmic Reticulum Stress and Disease (6 papers), Cellular transport and secretion (4 papers) and RNA and protein synthesis mechanisms (2 papers). Fabio Vilardi is often cited by papers focused on Endoplasmic Reticulum Stress and Disease (6 papers), Cellular transport and secretion (4 papers) and RNA and protein synthesis mechanisms (2 papers). Fabio Vilardi collaborates with scholars based in Germany, United Kingdom and United States. Fabio Vilardi's co-authors include Bernhard Dobberstein, Holger Lorenz, Blanche Schwappach, Vincenzo Favaloro, Anne Clancy, Stephen High, Milena Stephan, Andreas Janshoff, Matthias P. Mayer and Paweł Leźnicki and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Molecular Cell and The Journal of Immunology.

In The Last Decade

Fabio Vilardi

11 papers receiving 496 citations

Peers

Fabio Vilardi

MB

CB

GENET

IMMUN

ONCOL

Isha Nasa United States

Song Qu United States

V. Rao United States

Chris MacDonald United States

Steven J. Kaczowka United States

Jean-Christophe Larcher France

Miki Ii United States

T. Harada Japan

Thomas Zobel Germany

Kota Yanagitani Japan

Isha Nasa United States

Fabio Vilardi

458 ×1.2

MB

258 ×1.0

CB

30 ×0.4

GENET

22 ×0.4

IMMUN

70 ×1.7

ONCOL

Citations per year, relative to Fabio Vilardi Fabio Vilardi (= 1×) peers Isha Nasa

Countries citing papers authored by Fabio Vilardi

Since Specialization

Citations

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

Fields of papers citing papers by Fabio Vilardi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fabio Vilardi

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

All Works

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11 of 11 papers shown

1.

Unthan‐Fechner, Kirsten, Anne Clancy, Uri Weill, et al.. (2016). Mice lacking WRB reveal differential biogenesis requirements of tail-anchored proteins in vivo. Scientific Reports. 6(1). 39464–39464. 31 indexed citations

2.

Buentzel, Judith, Fabio Vilardi, Amelie S. Lotz‐Havla, Jutta Gärtner, & Sven Thoms. (2015). Conserved targeting information in mammalian and fungal peroxisomal tail-anchored proteins. Scientific Reports. 5(1). 17420–17420. 13 indexed citations

3.

Jamieson, Cara, et al.. (2015). Emery–Dreifuss muscular dystrophy mutations impair TRC40-mediated targeting of emerin to the inner nuclear membrane. Journal of Cell Science. 129(3). 502–516. 22 indexed citations

4.

Vilardi, Fabio, Milena Stephan, Anne Clancy, Andreas Janshoff, & Blanche Schwappach. (2014). WRB and CAML Are Necessary and Sufficient to Mediate Tail-Anchored Protein Targeting to the ER Membrane. PLoS ONE. 9(1). e85033–e85033. 53 indexed citations

5.

Schick, Markus, Stephanie N. Gates, Sheng Li, et al.. (2014). The Protein Targeting Factor Get3 Functions as ATP-Independent Chaperone under Oxidative Stress Conditions. Molecular Cell. 56(1). 116–127. 55 indexed citations

6.

Johnson, Nicholas, Fabio Vilardi, Sven Lang, et al.. (2012). TRC40 can deliver short secretory proteins to the Sec61 translocon. Journal of Cell Science. 125(18). 4414–4414. 3 indexed citations

7.

Johnson, Nicholas, Fabio Vilardi, Sven Lang, et al.. (2012). TRC40 can deliver short secretory proteins to the Sec61 translocon. Journal of Cell Science. 125(15). 3612–3620. 53 indexed citations

8.

Horst, Daniëlle, Vincenzo Favaloro, Fabio Vilardi, et al.. (2011). EBV Protein BNLF2a Exploits Host Tail-Anchored Protein Integration Machinery To Inhibit TAP. The Journal of Immunology. 186(6). 3594–3605. 37 indexed citations

9.

Vilardi, Fabio, Holger Lorenz, & Bernhard Dobberstein. (2011). WRB is the receptor for TRC40/Asna1-mediated insertion of tail-anchored proteins into the ER membrane. Journal of Cell Science. 124(8). 1301–1307. 95 indexed citations

10.

Favaloro, Vincenzo, et al.. (2010). Asna1/TRC40-mediated membrane insertion of tail-anchored proteins. Journal of Cell Science. 123(9). 1522–1530. 50 indexed citations

11.

Bozkurt, Günes, Goran Stjepanović, Fabio Vilardi, et al.. (2009). Structural insights into tail-anchored protein binding and membrane insertion by Get3. Proceedings of the National Academy of Sciences. 106(50). 21131–21136. 84 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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