Aiko Uemura

4.2k total citations · 1 hit paper
24 papers, 2.4k citations indexed

About

Aiko Uemura is a scholar working on Plant Science, Molecular Biology and Genetics. According to data from OpenAlex, Aiko Uemura has authored 24 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Plant Science, 12 papers in Molecular Biology and 7 papers in Genetics. Recurrent topics in Aiko Uemura's work include Genetic Mapping and Diversity in Plants and Animals (6 papers), Plant-Microbe Interactions and Immunity (5 papers) and Genomics and Phylogenetic Studies (4 papers). Aiko Uemura is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (6 papers), Plant-Microbe Interactions and Immunity (5 papers) and Genomics and Phylogenetic Studies (4 papers). Aiko Uemura collaborates with scholars based in Japan, United Kingdom and Australia. Aiko Uemura's co-authors include Ryohei Terauchi, Hiroki Takagi, Sophien Kamoun, Satoshi Natsume, Akira Abe, Muluneh Tamiru, Chikako Mitsuoka, Kentaro Yoshida, Hiroe Utsushi and Liliana M. Cano and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and The Plant Cell.

In The Last Decade

Aiko Uemura

24 papers receiving 2.4k citations

Hit Papers

QTL‐seq: rapid mapping of quantitative trait loci in rice... 2013 2026 2017 2021 2013 250 500 750

Peers

Aiko Uemura
Comparison fields: 5 of 80
  • Plant Science 2.0k
  • Molecular Biology 842
  • Genetics 738
  • Cell Biology 218
  • Food Science 73
Replace Hamid Ashrafi with:
Hamid Ashrafi United States
Noelle A. Barkley United States
Alexander Kozik United States
Parveen Chhuneja India
Muluneh Tamiru Japan
Leah K. McHale United States
Uri Lavi Israel
Burkhard Steuernagel United Kingdom
Concha Domingo Spain
Andrew Baumgarten United States
Hamid Ashrafi United States View profile →
Citations per field, relative to Aiko Uemura
Aiko Uemura · 1×
Citations per year, relative to Aiko Uemura
Aiko Uemura · 1×

Countries citing papers authored by Aiko Uemura

Since Specialization
Citations

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

Fields of papers citing papers by Aiko Uemura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aiko Uemura

This figure shows the co-authorship network connecting the top 25 collaborators of Aiko Uemura. A scholar is included among the top collaborators of Aiko Uemura 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 Uemura. Aiko Uemura 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
# Work Indexed citations
1 4
2 2
3 5
4 15
5 32
6 20
7 6
8 140
9 55
10 16
11 78
12 26
13 102
14 84
15 76
16
QTL‐seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations breakdown →
989
17 9
18 230
19 41
20 67

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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