Akane Kubota

1.7k total citations
25 papers, 1.2k citations indexed

About

Akane Kubota is a scholar working on Molecular Biology, Plant Science and Endocrine and Autonomic Systems. According to data from OpenAlex, Akane Kubota has authored 25 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 17 papers in Plant Science and 3 papers in Endocrine and Autonomic Systems. Recurrent topics in Akane Kubota's work include Plant Molecular Biology Research (17 papers), Light effects on plants (12 papers) and Photosynthetic Processes and Mechanisms (6 papers). Akane Kubota is often cited by papers focused on Plant Molecular Biology Research (17 papers), Light effects on plants (12 papers) and Photosynthetic Processes and Mechanisms (6 papers). Akane Kubota collaborates with scholars based in Japan, United States and South Korea. Akane Kubota's co-authors include Takato Imaizumi, Jae Sung Shim, Takayuki Kohchi, Kimitsune Ishizaki, Ryuichi Nishihama, Young Hun Song, Katsuyuki T. Yamato, Dianne Laboy Cintrón, Michael S. Kwon and Andrew J. Millar and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Akane Kubota

24 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Akane Kubota Japan 14 984 739 150 72 50 25 1.2k
Younousse Saidi Switzerland 13 890 0.9× 705 1.0× 88 0.6× 34 0.5× 26 0.5× 14 1.2k
Luca Rizzini Germany 6 1.5k 1.5× 1.1k 1.5× 157 1.0× 116 1.6× 16 0.3× 6 1.6k
Mitsumasa Hanaoka Japan 20 648 0.7× 1.0k 1.4× 178 1.2× 61 0.8× 7 0.1× 33 1.3k
Kazunari Nozue United States 14 1.7k 1.7× 1.3k 1.7× 105 0.7× 246 3.4× 12 0.2× 21 1.9k
Mika Teranishi Japan 17 565 0.6× 443 0.6× 103 0.7× 68 0.9× 16 0.3× 34 800
Motomu Endo Japan 18 1.2k 1.2× 854 1.2× 68 0.5× 25 0.3× 12 0.2× 35 1.3k
Amaury de Montaigu Germany 13 993 1.0× 959 1.3× 49 0.3× 40 0.6× 25 0.5× 18 1.3k
Davide Faggionato United States 7 826 0.8× 621 0.8× 82 0.5× 115 1.6× 8 0.2× 7 964
Matthew McCormack United States 11 2.0k 2.0× 1.0k 1.4× 50 0.3× 164 2.3× 15 0.3× 11 2.4k
Kumiko Miwa Japan 6 886 0.9× 769 1.0× 41 0.3× 83 1.2× 14 0.3× 6 1.0k

Countries citing papers authored by Akane Kubota

Since Specialization
Citations

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

Fields of papers citing papers by Akane Kubota

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Akane Kubota

This figure shows the co-authorship network connecting the top 25 collaborators of Akane Kubota. A scholar is included among the top collaborators of Akane Kubota 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 Akane Kubota. Akane Kubota 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
1.
Endo, Motomu, Masaki Ito, Akane Kubota, & Nozomu Takahashi. (2025). GEAR: an integrated atlas of gene expression dynamics in Arabidopsis thaliana. Nucleic Acids Research. 54(D1). D1711–D1719. 1 indexed citations
2.
Lee, Nayoung, et al.. (2023). Low temperature‐mediated repression and far‐red light‐mediated induction determine morning FLOWERING LOCUS T expression levels. Journal of Integrative Plant Biology. 66(1). 103–120. 7 indexed citations
3.
Kondo, Yohei, et al.. (2023). Circadian Clock Controls Root Hair Elongation through Long-Distance Communication. Plant and Cell Physiology. 64(11). 1289–1300. 6 indexed citations
4.
Yamauchi, Shota, Akane Kubota, Nozomu Takahashi, et al.. (2023). Root PRR7 Improves the Accuracy of the Shoot Circadian Clock through Nutrient Transport. Plant and Cell Physiology. 64(3). 352–362. 10 indexed citations
5.
Lee, Nayoung, Andrew K Hempton, Hiroshi Takagi, et al.. (2023). The FLOWERING LOCUS T gene expression is controlled by high‐irradiance response and external coincidence mechanism in long days in Arabidopsis. New Phytologist. 239(1). 208–221. 16 indexed citations
6.
Inoue, Keisuke, Minoru Kubo, Yuki Kondo, et al.. (2022). A guiding role of the Arabidopsis circadian clock in cell differentiation revealed by time-series single-cell RNA sequencing. Cell Reports. 40(2). 111059–111059. 16 indexed citations
7.
Kubota, Akane, et al.. (2019). Time-Series Single-Cell RNA-Seq Data Reveal Auxin Fluctuation during Endocycle. Plant and Cell Physiology. 61(2). 243–254. 12 indexed citations
8.
Seaton, Daniel D., et al.. (2018). Dawn and photoperiod sensing by phytochrome A. Proceedings of the National Academy of Sciences. 115(41). 10523–10528. 34 indexed citations
9.
Song, Young Hun, Akane Kubota, Michael S. Kwon, et al.. (2018). Molecular basis of flowering under natural long-day conditions in Arabidopsis. Nature Plants. 4(10). 824–835. 120 indexed citations
10.
Krahmer, Johanna, Greg S. Goralogia, Akane Kubota, et al.. (2018). Time‐resolved interaction proteomics of the GIGANTEA protein under diurnal cycles in Arabidopsis. FEBS Letters. 593(3). 319–338. 33 indexed citations
11.
Kubota, Akane, Shogo Ito, Jae Sung Shim, et al.. (2017). TCP4-dependent induction of CONSTANS transcription requires GIGANTEA in photoperiodic flowering in Arabidopsis. PLoS Genetics. 13(6). e1006856–e1006856. 97 indexed citations
12.
Kubota, Akane, Jae Sung Shim, & Takato Imaizumi. (2015). Natural variation in transcriptional rhythms modulates photoperiodic responses. Trends in Plant Science. 20(5). 259–261. 6 indexed citations
13.
Nishihama, Ryuichi, et al.. (2015). Phytochrome-mediated regulation of cell division and growth during regeneration and sporeling development in the liverwort Marchantia polymorpha. Journal of Plant Research. 128(3). 407–421. 60 indexed citations
14.
Kubota, Akane, et al.. (2014). Co-option of a photoperiodic growth-phase transition system during land plant evolution. Nature Communications. 5(1). 3668–3668. 87 indexed citations
15.
Kubota, Akane, et al.. (2013). EfficientAgrobacterium-Mediated Transformation of the LiverwortMarchantia polymorphaUsing Regenerating Thalli. Bioscience Biotechnology and Biochemistry. 77(1). 167–172. 215 indexed citations
16.
Ohta, Toshio, Akane Kubota, Matsuka Murakami, Ken‐ichi Otsuguro, & Shigeo Ito. (2005). P2X2receptors are essential for [Ca2+]iincreases in response to ATP in cultured rat myenteric neurons. American Journal of Physiology-Gastrointestinal and Liver Physiology. 289(5). G935–G948. 26 indexed citations
17.
Hisatomi, Akitaka, et al.. (1997). Elevated L-kynurenine level and its normalization by prednisolone in a patient with eosinophilia-myalgia syndrome.. PubMed. 88(1). 11–7. 3 indexed citations
18.
Nagato, Satoshi, et al.. (1996). E2011 a novel, selective and reversible inhibitor of monoamine oxidase type A.. Journal of Pharmacology and Experimental Therapeutics. 278(1). 243–251. 20 indexed citations
19.
Nakagawa, Yuichi, et al.. (1996). Detection of an Aberrant Fragment in Growth Hormone Gene Cluster in a Girl with Congenital Generalized Lipodystrophy. Hormone and Metabolic Research. 28(1). 23–26.
20.

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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