Virginia Pardo

43 total papers · 1.7k total citations
28 papers, 1.3k citations indexed

About

Virginia Pardo is a scholar working on Molecular Biology, Cancer Research and Epidemiology. According to data from OpenAlex, Virginia Pardo has authored 28 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 10 papers in Cancer Research and 9 papers in Epidemiology. Recurrent topics in Virginia Pardo's work include MicroRNA in disease regulation (7 papers), Liver Disease Diagnosis and Treatment (6 papers) and Protein Tyrosine Phosphatases (4 papers). Virginia Pardo is often cited by papers focused on MicroRNA in disease regulation (7 papers), Liver Disease Diagnosis and Treatment (6 papers) and Protein Tyrosine Phosphatases (4 papers). Virginia Pardo collaborates with scholars based in Spain, United States and Singapore. Virginia Pardo's co-authors include Ángela M. Valverde, Águeda González‐Rodríguez, Jordi Muntané, M. Pilar Valdecantos, Lisardo Boscá, Paloma Martı́n-Sanz, Carmelo García‐Monzón, Rafael Mayoral, Marco Corazzari and Mauro Piacentini and has published in prestigious journals such as Journal of Biological Chemistry, Molecular and Cellular Biology and Cancer Research.

In The Last Decade

Virginia Pardo

27 papers receiving 1.3k citations

Hit Papers

Impaired autophagic flux ... 2014 2026 2018 2022 2014 100 200 300 400

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Virginia Pardo 625 495 206 179 158 28 1.3k
Xiwen Xiong 711 1.1× 714 1.4× 181 0.9× 247 1.4× 181 1.1× 38 1.6k
Bilon Khambu 602 1.0× 376 0.8× 152 0.7× 146 0.8× 107 0.7× 36 1.1k
Sharon Manley 693 1.1× 446 0.9× 152 0.7× 117 0.7× 99 0.6× 18 1.2k
Yulia A. Nevzorova 721 1.2× 571 1.2× 157 0.8× 170 0.9× 142 0.9× 49 1.6k
Gaia Robino 658 1.1× 592 1.2× 99 0.5× 256 1.4× 129 0.8× 16 1.8k
Banumathi K. Cole 518 0.8× 577 1.2× 276 1.3× 282 1.6× 246 1.6× 26 1.7k
Chunjiong Wang 431 0.7× 512 1.0× 182 0.9× 234 1.3× 260 1.6× 26 1.4k
M. Sambasiva Rao 593 0.9× 685 1.4× 121 0.6× 228 1.3× 237 1.5× 33 1.6k
Françoise Pecker 455 0.7× 806 1.6× 153 0.7× 196 1.1× 193 1.2× 33 1.7k
M. Pilar Valdecantos 638 1.0× 387 0.8× 195 0.9× 247 1.4× 152 1.0× 26 1.2k

Countries citing papers authored by Virginia Pardo

Since Specialization
Citations

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

Fields of papers citing papers by Virginia Pardo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Virginia Pardo

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

All Works

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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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