Carlos Vay

256 total papers · 4.7k total citations
180 papers, 3.1k citations indexed

About

Carlos Vay is a scholar working on Endocrinology, Epidemiology and Molecular Medicine. According to data from OpenAlex, Carlos Vay has authored 180 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 77 papers in Endocrinology, 63 papers in Epidemiology and 63 papers in Molecular Medicine. Recurrent topics in Carlos Vay's work include Antibiotic Resistance in Bacteria (63 papers), Bacterial Identification and Susceptibility Testing (43 papers) and Infections and bacterial resistance (40 papers). Carlos Vay is often cited by papers focused on Antibiotic Resistance in Bacteria (63 papers), Bacterial Identification and Susceptibility Testing (43 papers) and Infections and bacterial resistance (40 papers). Carlos Vay collaborates with scholars based in Argentina, United States and Uruguay. Carlos Vay's co-authors include Àngela Famiglietti, Carlos M. Luna, Michael S. Niederman, Marisa Almuzara, Patrícia Vujacich, C Gherardi, Enrique C. Jolly, María Soledad Ramírez, Claudia Barberis and Gabriel Gutkind and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Carlos Vay

170 papers receiving 3.0k citations

Hit Papers

Impact of BAL Data on the... 1997 2026 2006 2016 1997 200 400 600

Author Peers

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

Author Last Decade Papers Cites
Carlos Vay 1.1k 1.1k 899 729 718 180 3.1k
D. Talon 1.2k 1.1× 758 0.7× 382 0.4× 623 0.9× 498 0.7× 137 3.0k
Marie‐Laure Joly‐Guillou 2.3k 2.2× 1.4k 1.3× 1.1k 1.2× 1.1k 1.6× 1.1k 1.5× 122 4.8k
Geert Claeys 831 0.8× 2.1k 2.0× 694 0.8× 1.1k 1.5× 270 0.4× 135 5.0k
Guillem Prats 1.4k 1.3× 1.9k 1.8× 1.2k 1.4× 490 0.7× 1.1k 1.5× 105 4.3k
Gerda Verschraegen 696 0.7× 1.6k 1.5× 686 0.8× 893 1.2× 261 0.4× 109 3.9k
C. Bollet 1.0k 1.0× 805 0.8× 884 1.0× 1.2k 1.6× 277 0.4× 84 3.8k
F. W. Goldstein 1.6k 1.5× 1.4k 1.3× 442 0.5× 637 0.9× 467 0.7× 119 4.0k
Catherine Branger 1.6k 1.5× 745 0.7× 1.1k 1.3× 693 1.0× 250 0.3× 70 3.1k
Àngela Famiglietti 860 0.8× 665 0.6× 612 0.7× 439 0.6× 238 0.3× 140 2.0k
Vincent O. Rotimi 1.5k 1.4× 1.1k 1.0× 789 0.9× 478 0.7× 165 0.2× 131 3.8k

Countries citing papers authored by Carlos Vay

Since Specialization
Citations

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

Fields of papers citing papers by Carlos Vay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Carlos Vay

This figure shows the co-authorship network connecting the top 25 collaborators of Carlos Vay. A scholar is included among the top collaborators of Carlos Vay 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 Carlos Vay. Carlos Vay 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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