Mayuko Ikeda

1.7k total citations · 1 hit paper
8 papers, 1.3k citations indexed

About

Mayuko Ikeda is a scholar working on Plant Science, Genetics and Molecular Biology. According to data from OpenAlex, Mayuko Ikeda has authored 8 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Plant Science, 5 papers in Genetics and 2 papers in Molecular Biology. Recurrent topics in Mayuko Ikeda's work include Genetic Mapping and Diversity in Plants and Animals (5 papers), Rice Cultivation and Yield Improvement (3 papers) and Plant Molecular Biology Research (2 papers). Mayuko Ikeda is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (5 papers), Rice Cultivation and Yield Improvement (3 papers) and Plant Molecular Biology Research (2 papers). Mayuko Ikeda collaborates with scholars based in Japan and United States. Mayuko Ikeda's co-authors include Makoto Matsuoka, Hidemi Kitano, Kotaro Miura, Kenji Asano, Motoyuki Ashikari, Atsushi Matsubara, Xian‐Jun Song, Koichiro Aya, Tokunori Hobo and Taiichiro Ookawa and has published in prestigious journals such as Nature Communications, Nature Genetics and Scientific Reports.

In The Last Decade

Mayuko Ikeda

8 papers receiving 1.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

OsSPL14 promotes panicle branching and higher grain productivity in rice

2010 815 citations Kotaro Miura, Mayuko Ikeda et al. Nature Genetics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mayuko Ikeda Japan	8	1.2k	605	416	135	41	8	1.3k
Lihui Li China	28	2.2k 1.8×	742 1.2×	249 0.6×	226 1.7×	49 1.2×	108	2.3k
Mary A. Rupe United States	8	840 0.7×	472 0.8×	381 0.9×	51 0.4×	36 0.9×	9	972
Ming Hao China	15	856 0.7×	232 0.4×	276 0.7×	83 0.6×	21 0.5×	73	938
Lixia Ku China	23	1.6k 1.3×	727 1.2×	572 1.4×	263 1.9×	21 0.5×	65	1.7k
Gunter Backes Denmark	21	1.1k 0.9×	428 0.7×	146 0.4×	123 0.9×	31 0.8×	46	1.2k
Andrew Steed United Kingdom	18	1.4k 1.2×	368 0.6×	168 0.4×	156 1.2×	37 0.9×	32	1.5k
Changling Huang China	17	716 0.6×	451 0.7×	233 0.6×	118 0.9×	13 0.3×	35	844
Song Lim Kim South Korea	17	1.2k 1.0×	496 0.8×	513 1.2×	39 0.3×	52 1.3×	35	1.3k
Sundeep Kumar India	13	754 0.6×	242 0.4×	95 0.2×	129 1.0×	31 0.8×	30	833
Raj Pasam Australia	13	688 0.6×	381 0.6×	76 0.2×	107 0.8×	19 0.5×	16	747

Countries citing papers authored by Mayuko Ikeda

Since Specialization

Citations

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

Fields of papers citing papers by Mayuko Ikeda

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mayuko Ikeda

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

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Ikeda, Mayuko, Masaru Murakami, Mikio Masuzawa, et al.. (2020). Regulatory expression of bone morphogenetic protein 6 by 2,2′-dipyridyl. Biochimica et Biophysica Acta (BBA) - General Subjects. 1864(8). 129610–129610. 11 indexed citations

2.

Ikeda, Mayuko, et al.. (2018). Comprehensive panicle phenotyping reveals that qSrn7/FZP influences higher-order branching. Scientific Reports. 8(1). 12511–12511. 27 indexed citations

3.

Ikeda, Mayuko, Kotaro Miura, Koichiro Aya, Hidemi Kitano, & Makoto Matsuoka. (2013). Genes offering the potential for designing yield-related traits in rice. Current Opinion in Plant Biology. 16(2). 213–220. 98 indexed citations

4.

Miura, Kotaro, Mayuko Ikeda, Atsushi Matsubara, et al.. (2010). OsSPL14 promotes panicle branching and higher grain productivity in rice. Nature Genetics. 42(6). 545–549. 815 indexed citations breakdown →

5.

Ookawa, Taiichiro, Tokunori Hobo, Masahiro Yano, et al.. (2010). New approach for rice improvement using a pleiotropic QTL gene for lodging resistance and yield. Nature Communications. 1(1). 132–132. 255 indexed citations

6.

Miura, Kotaro, Mayuko Ikeda, Atsushi Matsubara, et al.. (2010). OsSPL14 promotes panicle branching and higher grain productivity in rice. Nat Genet. 24 indexed citations

7.

Ikeda, Mayuko, Tomonori Takashi, Yosuke Shibata, et al.. (2010). Analysis of rice panicle traits and detection of QTLs using an image analyzing method. Breeding Science. 60(1). 55–64. 51 indexed citations

8.

Kato, Juntaro, et al.. (2008). Unreduced gametes are the major causal factor for the production of polyploid interspecific hybrids in Primula. Plant Biotechnology. 25(6). 521–528. 10 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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