Eva Sánchez

27 papers receiving 452 citations

Peers

Eva Sánchez
Comparison fields: 5 of 65
  • Modeling and Simulation 52
  • Public Health, Environmental and Occupational Health 214
  • Numerical Analysis 33
  • Genetics 107
  • Mathematical Physics 34
Replace Philipp Getto with:
Philipp Getto Germany
Zhong Zhao China
K. Kawasaki Japan
Radouane Yafia Morocco
Kjartan G. Magnússon Iceland
Sanling Yuan China
Betty Tang United States
Sepideh Mirrahimi France
Qihua Huang China
Eva Sánchez relative to Philipp Getto Germany Philipp Getto's profile →
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Citations per year

Countries citing papers authored by Eva Sánchez

Since Specialization
Citations

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

Fields of papers citing papers by Eva Sánchez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200556
2 199536
3 199535
4 200633
5 201028
6 200028
7 199726
8 201325
9 199925
10 200224
11 200724
12 200815
13 200015
14 201913
15 200112
16 199711
17 200710
18 20059
19 20068
20 20057

About Eva Sánchez

Eva Sánchez is a scholar working on Modeling and Simulation, Numerical Analysis, Aging, Public Health, Environmental and Occupational Health and Mathematical Physics, having authored 28 papers that have together received 466 indexed citations. Recurring topics across this work include Mathematical and Theoretical Epidemiology and Ecology Models (13 papers), Evolution and Genetic Dynamics (6 papers), Mathematical Biology Tumor Growth (6 papers), Pluripotent Stem Cells Research (5 papers), CRISPR and Genetic Engineering (4 papers), Numerical methods for differential equations (4 papers), Evolutionary Game Theory and Cooperation (4 papers) and Theoretical and Computational Physics (3 papers). The work is most often cited by research in Modeling and Simulation (52 citations), Public Health, Environmental and Occupational Health (214 citations), Numerical Analysis (33 citations), Genetics (107 citations) and Mathematical Physics (34 citations). Eva Sánchez has collaborated with scholars based in Spain, France and United States. Frequent co-authors include Rafael Bravo de la Parra, Pierre Auger, Ovide Arino, Carlos Simón, Diana Valbuena, Amparo Galán, Glenn F. Webb, António Pellicer, Janet Dyson and Rosanna Villella-Bressan. Their work appears in journals such as Reproductive BioMedicine Online, Mathematical Models and Methods in Applied Sciences, Differential and Integral Equations, Acta Biotheoretica and Mathematical Biosciences.

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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