Eduardo Raimondi

967 total citations
32 papers, 586 citations indexed

About

Eduardo Raimondi is a scholar working on Genetics, Immunology and Molecular Biology. According to data from OpenAlex, Eduardo Raimondi has authored 32 papers receiving a total of 586 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Genetics, 10 papers in Immunology and 7 papers in Molecular Biology. Recurrent topics in Eduardo Raimondi's work include Forensic and Genetic Research (16 papers), T-cell and B-cell Immunology (9 papers) and Immune Cell Function and Interaction (8 papers). Eduardo Raimondi is often cited by papers focused on Forensic and Genetic Research (16 papers), T-cell and B-cell Immunology (9 papers) and Immune Cell Function and Interaction (8 papers). Eduardo Raimondi collaborates with scholars based in Argentina, Portugal and Spain. Eduardo Raimondi's co-authors include Marcelo Fernández-Viña, Peter Šťastný, Ulises Toscanini, Marie Černá, Michela Falco, Armando Maccagno, Horácio Friedman, Leonor Gusmão, Antonio Salas and Domingo Casadei and has published in prestigious journals such as PLoS ONE, Philosophical Transactions of the Royal Society B Biological Sciences and Transplantation.

In The Last Decade

Eduardo Raimondi

31 papers receiving 561 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Eduardo Raimondi Argentina 12 309 219 86 82 78 32 586
Gary M. Troup United States 11 339 1.1× 157 0.7× 12 0.1× 79 1.0× 125 1.6× 22 657
E.M. Dauber Austria 12 45 0.1× 211 1.0× 34 0.4× 70 0.9× 150 1.9× 45 359
Tongmao Zhao United States 16 459 1.5× 132 0.6× 5 0.1× 136 1.7× 118 1.5× 47 756
Julia Pingel Germany 14 437 1.4× 67 0.3× 153 1.8× 291 3.5× 117 1.5× 27 715
J. Longás Valién Spain 10 342 1.1× 82 0.4× 6 0.1× 41 0.5× 72 0.9× 29 496
J. Procter United Kingdom 8 512 1.7× 27 0.1× 74 0.9× 52 0.6× 32 0.4× 11 640
Danielle Paixão-Cavalcante United Kingdom 15 467 1.5× 245 1.1× 27 0.3× 172 2.1× 170 2.2× 18 766
Antonio Arnaiz-Villena Spain 13 448 1.4× 105 0.5× 3 0.0× 41 0.5× 63 0.8× 35 597
Chunmei Shen China 20 179 0.6× 765 3.5× 8 0.1× 31 0.4× 557 7.1× 78 1.1k
L. Schenning Sweden 7 488 1.6× 140 0.6× 9 0.1× 34 0.4× 166 2.1× 7 662

Countries citing papers authored by Eduardo Raimondi

Since Specialization
Citations

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

Fields of papers citing papers by Eduardo Raimondi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eduardo Raimondi

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

All Works

20 of 20 papers shown
1.
Toscanini, Ulises, et al.. (2012). Evaluating Methods to Correct for Population Stratification when Estimating Paternity Indexes. PLoS ONE. 7(11). e49832–e49832. 11 indexed citations
2.
Toscanini, Ulises, Leonor Gusmão, Verónica Gomes, et al.. (2011). Male lineages in South American native groups: Evidence of M19 traveling south. American Journal of Physical Anthropology. 146(2). 188–196. 19 indexed citations
3.
Toscanini, Ulises, et al.. (2009). Genetic data of 10 X-STR in two Native American populations of Argentina. Forensic science international. Genetics supplement series. 2(1). 405–406. 1 indexed citations
4.
Toscanini, Ulises, Antonio Salas, Manuel García‐Magariños, Leonor Gusmão, & Eduardo Raimondi. (2009). Population stratification in Argentina strongly influences likelihood ratio estimates in paternity testing as revealed by a simulation-based approach. International Journal of Legal Medicine. 124(1). 63–69. 10 indexed citations
5.
Toscanini, Ulises, Leonor Gusmão, António Amorim, et al.. (2008). Y chromosome microsatellite genetic variation in two Native American populations from Argentina: Population stratification and mutation data. Forensic Science International Genetics. 2(4). 274–280. 31 indexed citations
6.
Toscanini, Ulises, Leonor Gusmão, António Amorim, et al.. (2006). Genetic variability of 17 Y chromosome STRs in two Native American populations from Argentina. International Congress Series. 1288. 154–155. 2 indexed citations
7.
Toscanini, Ulises, Leonor Gusmão, António Amorim, et al.. (2006). Testing for genetic structure in different urban Argentinian populations. Forensic Science International. 165(1). 35–40. 21 indexed citations
8.
Toscanini, Ulises, et al.. (2003). Data analysis of 10 STR loci in a population in the province of Neuquen, Argentina. International Congress Series. 1239. 239–242. 1 indexed citations
9.
Sánchez‐Diz, Paula, Leonor Gusmão, Sandra Beleza, et al.. (2003). Results of the GEP-ISFG collaborative study on two Y-STRs tetraplexes: GEPY I (DYS461, GATA C4, DYS437 and DYS438) and GEPY II (DYS460, GATA A10, GATA H4 and DYS439). Forensic Science International. 135(2). 158–162. 11 indexed citations
10.
Toscanini, Ulises, et al.. (2003). STR data for PowerPlex®16 System from Neuquen population, SW Argentina. Forensic Science International. 134(2-3). 219–221. 8 indexed citations
11.
Toscanini, Ulises, et al.. (2003). STR data for PowerPlex®16 System from Buenos Aires population, Argentina. Forensic Science International. 134(2-3). 222–224. 11 indexed citations
12.
Gusmão, Leonor, Paula Sánchez‐Diz, Cı́ntia Alves, et al.. (2003). Results of the GEP-ISFG collaborative study on the Y chromosome STRs GATA A10, GATA C4, GATA H4, DYS437, DYS438, DYS439, DYS460 and DYS461: population data. Forensic Science International. 135(2). 150–157. 10 indexed citations
13.
Pérez‐Rodríguez, Martha, Eduardo Raimondi, Steven G. E. Marsh, & J. Alejandro Madrigal. (2002). Identification of a new MICA allele, MICA*047. Tissue Antigens. 59(3). 216–218. 4 indexed citations
14.
15.
16.
Lázaro, A. M., et al.. (1997). Novel HLA-B35 subtypes. Human Immunology. 53(2). 148–155. 9 indexed citations
17.
Fernández-Viña, Marcelo, et al.. (1997). Dissimilar evolution of B‐locus versus A‐locus and class II loci of the HLA region in South American Indian tribes. Tissue Antigens. 50(3). 233–250. 53 indexed citations
18.
Fernández-Viña, Marcelo, Michela Falco, Marie Černá, et al.. (1994). DQA1∗03 subtypes have different associations with DRB1 and DQB1 alleles. Human Immunology. 39(4). 290–298. 18 indexed citations
19.
Černá, Marie, Michela Falco, Horácio Friedman, et al.. (1993). Differences in HLA class II alleles of isolated South American Indian populations from Brazil and Argentina. Human Immunology. 37(4). 213–220. 120 indexed citations
20.
Falco, Michela, et al.. (1992). HLA class II alleles in South American Indians reflect their ancient migratory movements. Human Immunology. 34(1). 19–19. 2 indexed citations

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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