Isabel Cervera

982 total citations
22 papers, 208 citations indexed

About

Isabel Cervera is a scholar working on Immunology, Infectious Diseases and Epidemiology. According to data from OpenAlex, Isabel Cervera has authored 22 papers receiving a total of 208 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Immunology, 5 papers in Infectious Diseases and 3 papers in Epidemiology. Recurrent topics in Isabel Cervera's work include T-cell and B-cell Immunology (11 papers), Immune Cell Function and Interaction (11 papers) and Reproductive System and Pregnancy (7 papers). Isabel Cervera is often cited by papers focused on T-cell and B-cell Immunology (11 papers), Immune Cell Function and Interaction (11 papers) and Reproductive System and Pregnancy (7 papers). Isabel Cervera collaborates with scholars based in Spain, Mexico and United States. Isabel Cervera's co-authors include Clara Espitia, Raúl Mancilla, Ramón A. González, Jorge Martı́nez-Laso, Ángela Román, Miguel A. Herráiz, Iciar Rodríguez-Avial, Juan J. Picazo, J.A. Vidart and Juan Antonio Sáez Nieto and has published in prestigious journals such as Human Molecular Genetics, Frontiers in Immunology and Journal of General Virology.

In The Last Decade

Isabel Cervera

21 papers receiving 194 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Isabel Cervera Spain 7 122 79 68 42 34 22 208
Makoto Kamada Japan 10 96 0.8× 24 0.3× 187 2.8× 28 0.7× 18 0.5× 22 283
Barbara Guarino Switzerland 4 143 1.2× 74 0.9× 251 3.7× 19 0.5× 18 0.5× 5 314
Magilé Fonseca Cuba 11 224 1.8× 59 0.7× 120 1.8× 256 6.1× 13 0.4× 24 411
Joan O. Ngwuta United States 6 193 1.6× 60 0.8× 286 4.2× 12 0.3× 32 0.9× 6 363
Marilyn J. August United States 10 121 1.0× 71 0.9× 273 4.0× 20 0.5× 16 0.5× 15 317
Chompoonut Auphimai Thailand 14 312 2.6× 50 0.6× 131 1.9× 37 0.9× 64 1.9× 26 438
Lai Heng Hung Cuba 9 179 1.5× 42 0.5× 104 1.5× 214 5.1× 11 0.3× 11 305
Dimitra Klapsa United Kingdom 10 337 2.8× 48 0.6× 89 1.3× 160 3.8× 14 0.4× 19 435
María Piñana Spain 13 212 1.7× 14 0.2× 202 3.0× 62 1.5× 24 0.7× 27 353
Juanjie Tang United States 10 282 2.3× 49 0.6× 77 1.1× 8 0.2× 49 1.4× 13 346

Countries citing papers authored by Isabel Cervera

Since Specialization
Citations

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

Fields of papers citing papers by Isabel Cervera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Isabel Cervera

This figure shows the co-authorship network connecting the top 25 collaborators of Isabel Cervera. A scholar is included among the top collaborators of Isabel Cervera 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 Isabel Cervera. Isabel Cervera 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.
Martı́nez-Laso, Jorge, et al.. (2025). Truncated IFI16 mRNA transcripts can control its viral DNA defense activity. Molecular Immunology. 183. 137–144.
2.
Martı́nez-Laso, Jorge, et al.. (2024). Characterisation of LGP2 complex multitranscript system in humans: role in the innate immune response and evolution from non-human primates. Human Molecular Genetics. 34(1). 11–20. 1 indexed citations
3.
González-Pérez, María, María Montes‐Casado, Patricia Conde, et al.. (2022). Development of Potent Cellular and Humoral Immune Responses in Long-Term Hemodialysis Patients After 1273-mRNA SARS-CoV-2 Vaccination. Frontiers in Immunology. 13. 845882–845882. 5 indexed citations
4.
Velasco, Juan Carlos, et al.. (2018). Actuaciones para mejorar el estado de conservación de los ciprínidos ibéricos en la provincia de Salamanca. 68–72. 1 indexed citations
5.
Cervera, Isabel, et al.. (2015). Identification of the novel HLA‐DQB1*03:03:02:04 allele in a Spanish individual. Tissue Antigens. 85(3). 215–216. 1 indexed citations
6.
Cervera, Isabel, et al.. (2014). Different patterns of A*80:01:01:01 allele generation based on exon or intron sequences. Tissue Antigens. 85(1). 58–67. 2 indexed citations
7.
Martı́nez-Laso, Jorge, et al.. (2012). Promoter sequences confirm the three different evolutionary lineages described for HLA-G. Human Immunology. 74(3). 383–388. 12 indexed citations
8.
Cervera, Isabel, et al.. (2011). The novel HLA‐G*01:03:01:02 allele differs from G*01:03:01:01 by a possible inversion event in intron 3. Tissue Antigens. 78(2). 159–160. 2 indexed citations
9.
Martı́nez-Laso, Jorge, et al.. (2011). Polymorphism of the HLA-B*15 group of alleles is generated following 5 lineages of evolution. Human Immunology. 72(5). 412–421. 5 indexed citations
10.
Cervera, Isabel, et al.. (2010). A new allele, HLA-G*010120, is generated by a recombination event between HLA-G*01010101/02 and HLA-G*01010201. Tissue Antigens. 75(6). 738–740. 2 indexed citations
11.
Cervera, Isabel, et al.. (2010). Human leukocyte antigen–G allele polymorphisms have evolved following three different evolutionary lineages based on intron sequences. Human Immunology. 71(11). 1109–1115. 10 indexed citations
12.
Cervera, Isabel, et al.. (2010). The HLA-B*83:01 allele is generated by a gene conversion event including whole of exon 2 and partial introns 1 and 2 between B*44 and B*56 alleles. International Journal of Immunogenetics. 38(1). 73–75. 2 indexed citations
13.
Román, Ángela, et al.. (2009). Heterogeneous expression of HLA-G1, -G2, -G5, -G6, and -G7 in myeloid and plasmacytoid dendritic cells isolated from umbilical cord blood. Human Immunology. 70(2). 104–109. 12 indexed citations
14.
Cervera, Isabel, Miguel A. Herráiz, Ángela Román, J.A. Vidart, & Jorge Martı́nez-Laso. (2009). The novel HLA‐G*01010302 allele differs from G*01010301 by a single nucleotide change in intron 5. Tissue Antigens. 74(5). 463–464. 3 indexed citations
15.
Román, Ángela, Isabel Cervera, Miguel A. Herráiz, J.A. Vidart, & Jorge Martı́nez-Laso. (2009). A new allele, HLA‐G*01010106, with changes in intron 2. Tissue Antigens. 74(3). 270–271. 4 indexed citations
16.
Martı́nez-Laso, Jorge, et al.. (2009). Diversity of the G3 genes of human rotaviruses in isolates from Spain from 2004 to 2006: cross-species transmission and inter-genotype recombination generates alleles. Journal of General Virology. 90(4). 935–943. 33 indexed citations
17.
Martı́nez-Laso, Jorge, et al.. (2008). Phylogeny of G9 rotavirus genotype: A possible explanation of its origin and evolution. Journal of Clinical Virology. 44(1). 52–57. 19 indexed citations
18.
Román, Ángela, et al.. (2007). Generation of HLA-B*1516/B*1567/B*1595 and B*1517 alleles (B15 specific group) by transpecies evolution. Human Immunology. 68(12). 1001–1008. 4 indexed citations
19.
20.
Espitia, Clara, Isabel Cervera, Ramón A. González, & Raúl Mancilla. (1989). A 38-kD Mycobacterium tuberculosis antigen associated with infection. Its isolation and serologic evaluation.. PubMed. 77(3). 373–7. 77 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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