Carmen Gelpí

66 total papers · 1.5k total citations
53 papers, 1.1k citations indexed

About

Carmen Gelpí is a scholar working on Pathology and Forensic Medicine, Rheumatology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Carmen Gelpí has authored 53 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Pathology and Forensic Medicine, 15 papers in Rheumatology and 13 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Carmen Gelpí's work include Monoclonal and Polyclonal Antibodies Research (13 papers), Autoimmune Bullous Skin Diseases (12 papers) and T-cell and B-cell Immunology (8 papers). Carmen Gelpí is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (13 papers), Autoimmune Bullous Skin Diseases (12 papers) and T-cell and B-cell Immunology (8 papers). Carmen Gelpí collaborates with scholars based in Spain, United States and Mexico. Carmen Gelpí's co-authors include J. L. Rodríguez-Sánchez, John Hardin, Erik J. Sontheimer, C. Juárez, Albert J. Czaja, Maria Inácia Estevão-Costa, Sílvia Vidal, María Ángeles Martínez, María A. Barnadas and Tsuneyo Mimori and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Experimental Medicine and The Journal of Immunology.

In The Last Decade

Carmen Gelpí

52 papers receiving 1.0k citations

Author Peers

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

Author Last Decade Papers Cites
Carmen Gelpí 403 381 312 215 208 53 1.1k
Gerður Gröndal 375 0.9× 865 2.3× 173 0.6× 175 0.8× 704 3.4× 52 1.4k
Fengchun Zhang 214 0.5× 437 1.1× 196 0.6× 143 0.7× 306 1.5× 68 1.2k
Calypso Barbatis 246 0.6× 176 0.5× 136 0.4× 296 1.4× 232 1.1× 57 1.3k
Eva Balada 368 0.9× 619 1.6× 138 0.4× 425 2.0× 605 2.9× 45 1.4k
Serena Fasano 138 0.3× 591 1.6× 155 0.5× 144 0.7× 414 2.0× 44 976
Andrea Fava 237 0.6× 529 1.4× 296 0.9× 193 0.9× 455 2.2× 32 1.1k
Makoto Sueishi 189 0.5× 374 1.0× 97 0.3× 222 1.0× 294 1.4× 50 1.0k
Chanyuan Wu 345 0.9× 502 1.3× 124 0.4× 205 1.0× 187 0.9× 66 942
Gabriella Morozzi 150 0.4× 959 2.5× 264 0.8× 189 0.9× 489 2.4× 57 1.4k
Masashi Akizuki 456 1.1× 572 1.5× 241 0.8× 236 1.1× 302 1.5× 43 1.2k

Countries citing papers authored by Carmen Gelpí

Since Specialization
Citations

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

Fields of papers citing papers by Carmen Gelpí

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Carmen Gelpí

This figure shows the co-authorship network connecting the top 25 collaborators of Carmen Gelpí. A scholar is included among the top collaborators of Carmen Gelpí 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 Carmen Gelpí. Carmen Gelpí 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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2026