M Martín-Ayuso

2.2k total citations
10 papers, 280 citations indexed

About

M Martín-Ayuso is a scholar working on Hematology, Immunology and Molecular Biology. According to data from OpenAlex, M Martín-Ayuso has authored 10 papers receiving a total of 280 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Hematology, 6 papers in Immunology and 3 papers in Molecular Biology. Recurrent topics in M Martín-Ayuso's work include Multiple Myeloma Research and Treatments (5 papers), T-cell and B-cell Immunology (4 papers) and Platelet Disorders and Treatments (3 papers). M Martín-Ayuso is often cited by papers focused on Multiple Myeloma Research and Treatments (5 papers), T-cell and B-cell Immunology (4 papers) and Platelet Disorders and Treatments (3 papers). M Martín-Ayuso collaborates with scholars based in Spain, Netherlands and Czechia. M Martín-Ayuso's co-authors include Alberto Órfão, Júlia Almeida, Martín Pérez‐Andrés, Jesús F. San Miguel, Josefina Galende, Guillermo Martín–Núñez, José‐Ángel Hernández‐Rivas, Gema Mateo, Marı́a Jesús Moro and Delgado Rodríguez and has published in prestigious journals such as Cancer, International Journal of Cancer and Journal of Immunological Methods.

In The Last Decade

M Martín-Ayuso

10 papers receiving 274 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M Martín-Ayuso Spain 9 164 127 110 66 54 10 280
M. de Jesús Gallegos Santiago Spain 9 164 1.0× 81 0.6× 146 1.3× 57 0.9× 67 1.2× 11 334
Natalie Schub Germany 8 164 1.0× 88 0.7× 56 0.5× 143 2.2× 28 0.5× 21 292
Elisabetta Calistri Italy 7 205 1.3× 65 0.5× 66 0.6× 111 1.7× 83 1.5× 14 308
Stephan Bohl Germany 8 159 1.0× 89 0.7× 176 1.6× 56 0.8× 39 0.7× 16 329
Mingqiang Hua China 13 154 0.9× 211 1.7× 234 2.1× 57 0.9× 26 0.5× 18 393
Naomi Kawashima Japan 8 260 1.6× 75 0.6× 129 1.2× 98 1.5× 75 1.4× 37 369
Simanta Pathak United States 9 62 0.4× 210 1.7× 121 1.1× 86 1.3× 29 0.5× 12 371
Diego Quinones Raffo United States 9 152 0.9× 125 1.0× 83 0.8× 44 0.7× 72 1.3× 17 304
Maria Dimou Greece 11 182 1.1× 79 0.6× 146 1.3× 113 1.7× 153 2.8× 51 396
Stephan Schulz United States 2 165 1.0× 293 2.3× 44 0.4× 60 0.9× 29 0.5× 2 404

Countries citing papers authored by M Martín-Ayuso

Since Specialization
Citations

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

Fields of papers citing papers by M Martín-Ayuso

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M Martín-Ayuso

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

All Works

10 of 10 papers shown
1.
Flores‐Montero, Juan, Tomáš Kalina, Luzalba Sanoja-Flores, et al.. (2019). Fluorochrome choices for multi-color flow cytometry. Journal of Immunological Methods. 475. 112618–112618. 31 indexed citations
2.
Velden, Vincent H. J. van der, Juan Flores‐Montero, Martín Pérez‐Andrés, et al.. (2017). Optimization and testing of dried antibody tube: The EuroFlow LST and PIDOT tubes as examples. Journal of Immunological Methods. 475. 112287–112287. 25 indexed citations
3.
Böttcher, Sebastian, Vincent H. J. van der Velden, Matthias Ritgen, et al.. (2017). Lot-to-lot stability of antibody reagents for flow cytometry. Journal of Immunological Methods. 475. 112294–112294. 22 indexed citations
4.
Blanco, Elena, Martín Pérez‐Andrés, Luzalba Sanoja-Flores, et al.. (2017). Selection and validation of antibody clones against IgG and IgA subclasses in switched memory B-cells and plasma cells. Journal of Immunological Methods. 475. 112372–112372. 16 indexed citations
5.
Pérez‐Andrés, Martín, Júlia Almeida, M Martín-Ayuso, et al.. (2008). Soluble and membrane levels of molecules involved in the interaction between clonal plasma cells and the immunological microenvironment in multiple myeloma and their association with the characteristics of the disease. International Journal of Cancer. 124(2). 367–375. 20 indexed citations
6.
Martín-Ayuso, M, Júlia Almeida, Martín Pérez‐Andrés, et al.. (2008). Peripheral Blood Dendritic Cell Subsets from Patients with Monoclonal Gammopathies Show an Abnormal Distribution and Are Functionally Impaired. The Oncologist. 13(1). 82–92. 19 indexed citations
7.
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Pérez‐Andrés, Martín, Júlia Almeida, M Martín-Ayuso, et al.. (2005). Interaction between clonal plasma cells and the immune system in plasma cell dyscrasias.. PubMed. 18(2). 161–5. 4 indexed citations
10.
Hernández-Campo, Pilar, M Martín-Ayuso, Júlia Almeida, Antonio López, & Alberto Órfão. (2002). Comparative analysis of different flow cytometry‐based immunophenotypic methods for the analysis of CD59 and CD55 expression on major peripheral blood cell subsets. Cytometry. 50(3). 191–201. 28 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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