Aiko M. Tan

15 total papers · 1.3k total citations
15 papers, 1.1k citations indexed

About

Aiko M. Tan is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Cognitive Neuroscience. According to data from OpenAlex, Aiko M. Tan has authored 15 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cellular and Molecular Neuroscience, 5 papers in Molecular Biology and 4 papers in Cognitive Neuroscience. Recurrent topics in Aiko M. Tan's work include Neuroscience and Neuropharmacology Research (8 papers), Memory and Neural Mechanisms (4 papers) and Receptor Mechanisms and Signaling (3 papers). Aiko M. Tan is often cited by papers focused on Neuroscience and Neuropharmacology Research (8 papers), Memory and Neural Mechanisms (4 papers) and Receptor Mechanisms and Signaling (3 papers). Aiko M. Tan collaborates with scholars based in United States, Brazil and Japan. Aiko M. Tan's co-authors include Deborah M. Finch, Luiz E. Mello, Ésper A. Cavalheiro, Thomas L. Babb, James K. Pretorius, John Gigg, Karen H. Gylys, Gregory M. Cole, Jeffrey A. Fein and Nigel T. Maidment and has published in prestigious journals such as Journal of Neuroscience, Brain Research and CHEST Journal.

In The Last Decade

Aiko M. Tan

15 papers receiving 1.1k citations

Hit Papers

Circuit Mechanisms of Sei... 1993 2026 2004 2015 1993 100 200 300 400 500

Author Peers

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

Author Last Decade Papers Cites
Aiko M. Tan 843 360 277 261 191 15 1.1k
Ailing A. Lie 769 0.9× 494 1.4× 198 0.7× 299 1.1× 100 0.5× 21 1.1k
Louis Scheurer 853 1.0× 596 1.7× 140 0.5× 192 0.7× 149 0.8× 22 1.3k
A‐Min Huang 409 0.5× 254 0.7× 168 0.6× 118 0.5× 197 1.0× 20 1.0k
Kevin T. Gobeske 414 0.5× 443 1.2× 318 1.1× 113 0.4× 138 0.7× 17 1.2k
Véronique Riban 532 0.6× 262 0.7× 161 0.6× 324 1.2× 123 0.6× 17 982
Maria Amalia Di Castro 699 0.8× 340 0.9× 270 1.0× 112 0.4× 215 1.1× 27 1.2k
Corinne Brana 538 0.6× 433 1.2× 122 0.4× 165 0.6× 140 0.7× 20 1.0k
Lincoln F. Ramirez 873 1.0× 296 0.8× 248 0.9× 485 1.9× 94 0.5× 16 1.3k
E Sanabria 740 0.9× 393 1.1× 253 0.9× 352 1.3× 100 0.5× 26 1.0k
Marta Gómez‐Gonzalo 1.0k 1.2× 388 1.1× 423 1.5× 159 0.6× 199 1.0× 20 1.4k

Countries citing papers authored by Aiko M. Tan

Since Specialization
Citations

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

Fields of papers citing papers by Aiko M. Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aiko M. Tan

This figure shows the co-authorship network connecting the top 25 collaborators of Aiko M. Tan. A scholar is included among the top collaborators of Aiko M. Tan 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 Aiko M. Tan. Aiko M. Tan 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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