María Á. Risalde

87 papers receiving 1.5k citations

Peers

María Á. Risalde
Comparison fields: 5 of 59
  • Hepatology 321
  • Infectious Diseases 435
  • Animal Science and Zoology 198
  • Parasitology 109
  • Agronomy and Crop Science 103
Replace Jae‐Ku Oem with:
Jae‐Ku Oem South Korea
Melinda K. Rostal United States
Renate Wernery United Arab Emirates
Mario Ziller Germany
Kurt J. Vandegrift United States
Olivier Bourry France
Francesco Tolari Italy
Andreas Hlinak Germany
Maurizio Mazzei Italy
Péter Pankovics Hungary
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Citations per year

Countries citing papers authored by María Á. Risalde

Since Specialization
Citations

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

Fields of papers citing papers by María Á. Risalde

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by María Á. Risalde. 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 María Á. Risalde. The network helps show where María Á. Risalde may publish in the future.

Co-authors

The 25 scholars most cited alongside María Á. Risalde, 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 María Á. Risalde Line = papers co-authored together María Á. Risalde links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 89 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201782
2 202164
3 201763
4 201758
5 201948
6 201141
7 201741
8 201836
9 202035
10 201831
11 201931
12 201829
13 202029
14 201828
15 202028
16 201727
17 201827
18 201926
19 202326
20 200925

About María Á. Risalde

María Á. Risalde is a scholar working on Hepatology, Infectious Diseases, Animal Science and Zoology, Parasitology and Small Animals, having authored 89 papers that have together received 1.5k indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (23 papers), Hepatitis Viruses Studies and Epidemiology (20 papers), Animal Virus Infections Studies (15 papers), Vector-Borne Animal Diseases (7 papers), Animal Disease Management and Epidemiology (4 papers), Animal health and immunology (4 papers), Parasitic Infections and Diagnostics (3 papers) and Mosquito-borne diseases and control (3 papers). The work is most often cited by research in Hepatology (321 citations), Infectious Diseases (435 citations), Animal Science and Zoology (198 citations), Parasitology (109 citations) and Agronomy and Crop Science (103 citations). María Á. Risalde has collaborated with scholars based in Spain, United States and Italy. Frequent co-authors include José Carlos Gómez Villamandos, Christian Gortázar, Ignacio García‐Bocanegra, Verónica Molina-Hernández, Pedro José Sánchez-Cordón, Miriam Pedrera, Antonio Rivero‐Juárez, Mario Frías, Antonio Rivero Román and Pedro López‐López. Their work appears in journals such as Transboundary and Emerging Diseases, Veterinary Research, Veterinary Microbiology, Zoonoses and Public Health and Preventive Veterinary Medicine.

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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