Fernando Esperón

74 papers receiving 1.2k citations

Peers

Fernando Esperón
Comparison fields: 5 of 81
  • Parasitology 305
  • Molecular Medicine 132
  • Pollution 201
  • Microbiology 93
  • Virology 71
Replace Marion Vittecoq with:
Marion Vittecoq France
Andrew M. Ramey United States
Irene Zorrilla Spain
Rafael A. Molina‐López Spain
Gregorio Mentaberre Spain
Dominic A. Travis United States
Julius D. Keyyu Tanzania
Kristin Mühldorfer Germany
Sarah M. Hazel United Kingdom
Lawrence Mugisha Uganda
Fernando Esperón relative to Marion Vittecoq France Marion Vittecoq's profile →
Citations per field
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Citations per year

Countries citing papers authored by Fernando Esperón

Since Specialization
Citations

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

Fields of papers citing papers by Fernando Esperón

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Fernando Esperón, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Fernando Esperón Line = papers co-authored together Fernando Esperón links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 77 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200867
2 200753
3 201050
4 201548
5 201543
6 201342
7 201440
8 202036
9 202035
10 201934
11 201032
12 201631
13 201029
14 201229
15 201028
16 201728
17 202125
18 202025
19 201123
20 201223

About Fernando Esperón

Fernando Esperón is a scholar working on Parasitology, Epidemiology, Ecology, Infectious Diseases and Pollution, having authored 77 papers that have together received 1.2k indexed citations. Recurring topics across this work include Marine animal studies overview (14 papers), Aquaculture disease management and microbiota (14 papers), Pharmaceutical and Antibiotic Environmental Impacts (13 papers), Toxoplasma gondii Research Studies (11 papers), Animal Virus Infections Studies (10 papers), Herpesvirus Infections and Treatments (10 papers), Virus-based gene therapy research (7 papers) and Turtle Biology and Conservation (7 papers). The work is most often cited by research in Parasitology (305 citations), Molecular Medicine (132 citations), Pollution (201 citations), Microbiology (93 citations) and Virology (71 citations). Fernando Esperón has collaborated with scholars based in Spain, Brazil and Chile. Frequent co-authors include José Manuel Sánchez‐Vizcaíno, Ana de la Torre, Antonio Fernández, Javier Millán, Carlos Sacristán, Manuel Arbelo, Matilde Carballo, Mariano Higes, Daniel García‐Párraga and Deborah Kukielka. Their work appears in journals such as Transboundary and Emerging Diseases, Diseases of Aquatic Organisms, Frontiers in Veterinary Science, The Science of The Total Environment and Scientific Reports.

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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