M. Vaiman

2.8k citations
83 papers · 1.9k · h-index 27

Impact in

    • Microbial infections and disease research
  • Immunology top 5%
    • T-cell and B-cell Immunology
    • Immune Cell Function and Interaction

Papers in

    • Genetic and phenotypic traits in livestock 11
    • Genetic Mapping and Diversity in Plants and Animals 8
    • Animal Genetics and Reproduction 8

M. Vaiman

83 papers receiving 1.9k citations

Peers

M. Vaiman
Comparison fields: 5 of 88
  • Microbiology 271
  • Immunology 669
  • Animal Science and Zoology 274
  • Genetics 722
  • Agronomy and Crop Science 251
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M R Brandon Australia
Ángel Ezquerra Spain
S. Lazáry Switzerland
Anne Eugster United States
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Citations per year

Countries citing papers authored by M. Vaiman

Since Specialization
Citations

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

Fields of papers citing papers by M. Vaiman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 83 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999127
2 197895
3 199581
4 197074
5 200162
6 199561
7 199560
8 200158
9 198857
10 199353
11 198549
12 199548
13 198746
14 197944
15
Assignment of MHC in swine to chromosome 7 by in situ hybridization and serological typing.
198442
16 198240
17 199838
18 199238
19 199735
20 199133

About M. Vaiman

M. Vaiman is a scholar working on Molecular Biology, Genetics, Immunology, Animal Science and Zoology and Microbiology, having authored 83 papers that have together received 1.9k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (13 papers), Microbial infections and disease research (13 papers), Genetic and phenotypic traits in livestock (11 papers), Animal Virus Infections Studies (10 papers), Immune Cell Function and Interaction (9 papers), Genetic Mapping and Diversity in Plants and Animals (8 papers), Animal Genetics and Reproduction (8 papers) and Xenotransplantation and immune response (7 papers). The work is most often cited by research in Microbiology (271 citations), Immunology (669 citations), Animal Science and Zoology (274 citations), Genetics (722 citations) and Agronomy and Crop Science (251 citations). M. Vaiman has collaborated with scholars based in France, Morocco and United States. Frequent co-authors include Christine Renard, P. Chardon, Patrick Chardon, Claudine Geffrotin, Claire Rogel Gaillard, Marek Kirszenbaum, Alain Billault, Hubert H. Levéziel, Martin Hessing and Laurence Cattolico. Their work appears in journals such as Animal Genetics, Immunogenetics, Mammalian Genome, Transplantation and International Journal of Immunogenetics.

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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