Ikuri Álvarez-Maya

16 papers receiving 748 citations

Hit Papers

hGFAP‐cre transgenic mice for manipulation of glial and n...20012026200920172001100200300400500

Peers

Ikuri Álvarez-Maya
Comparison fields: 5 of 76
  • Molecular Biology 452
  • Developmental Neuroscience 182
  • Cellular and Molecular Neuroscience 170
  • Genetics 132
  • Cancer Research 99
Replace Martine Geraerts with:
Martine Geraerts Belgium
Matthieu Vermeren United Kingdom
Taito Matsuda Japan
Ralitsa Petrova United States
Daniel Haag Germany
Emma Smith United Kingdom
Sean Nygaard United States
Prithi Rajan United States
Fabien Agenès France
Naihong Yan China
Ikuri Álvarez-Maya relative to Martine Geraerts Belgium Martine Geraerts's profile →
Citations per field
00.5×2.7×
Martine Geraerts · 1×
Citations per year

Countries citing papers authored by Ikuri Álvarez-Maya

Since Specialization
Citations

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

Fields of papers citing papers by Ikuri Álvarez-Maya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ikuri Álvarez-Maya. 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 Ikuri Álvarez-Maya. The network helps show where Ikuri Álvarez-Maya may publish in the future.

Co-authorship network of co-authors of Ikuri Álvarez-Maya

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

All Works

17 of 17 papers shown
#WorkIndexed citations
1 1
2 0
3 2
4 3
5 7
6 1
7 4
8 12
9 34
10 6
11 7
12 55
13 14
14 13
15
hGFAP‐cre transgenic mice for manipulation of glial and neuronal function in vivobreakdown →
512
16 35
17 50

About Ikuri Álvarez-Maya

Ikuri Álvarez-Maya is a scholar working on General Dentistry, Infectious Diseases and Developmental Neuroscience, having authored 17 papers that have together received 756 indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (4 papers), Mycobacterium research and diagnosis (3 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). The work is most often cited by research in Developmental Neuroscience (182 citations), Cellular and Molecular Neuroscience (170 citations) and Neurology (64 citations). Ikuri Álvarez-Maya has collaborated with scholars based in Mexico, Czechia and United States. Frequent co-authors include Klaus Willecke, Albee Messing, Lang Zhuo, Martin Theis, Michael Brenner, Marco Antonio Meraz‐Ríos, Iván Navarro-Quiroga, Daniel Martínez‐Fong, J.A. Caminero Luna and José‐Antonio Arias‐Montaño. Their work appears in journals such as Molecules, European Journal of Immunology and International Journal of Environmental Research and Public Health.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026