Tatsuo Kakimoto

13.6k total citations · 5 hit papers
60 papers, 10.1k citations indexed

About

Tatsuo Kakimoto is a scholar working on Plant Science, Molecular Biology and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Tatsuo Kakimoto has authored 60 papers receiving a total of 10.1k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Plant Science, 48 papers in Molecular Biology and 2 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Tatsuo Kakimoto's work include Plant Molecular Biology Research (45 papers), Plant Reproductive Biology (36 papers) and Plant nutrient uptake and metabolism (15 papers). Tatsuo Kakimoto is often cited by papers focused on Plant Molecular Biology Research (45 papers), Plant Reproductive Biology (36 papers) and Plant nutrient uptake and metabolism (15 papers). Tatsuo Kakimoto collaborates with scholars based in Japan, United States and Czechia. Tatsuo Kakimoto's co-authors include Kaori Miyawaki, Masato T. Kanemaki, Kohei Nishimura, Kazuo Shinozaki, Tatsuo Fukagawa, Haruhiko Takisawa, Masayuki Higuchi, Tomohiko Kato, Satoshi Tabata and Keiko U. Torii and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Tatsuo Kakimoto

60 papers receiving 9.9k citations

Hit Papers

An auxin-based degron system for the rapid depletion of p... 2001 2026 2009 2017 2009 2001 2011 2004 2003 250 500 750 1000
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.

  1. An auxin-based degron system for the rapid depletion of proteins in nonplant cells
    2009 1.2k citations Tatsuo Kakimoto et al. profile →
  2. Identification of CRE1 as a cytokinin receptor from Arabidopsis
    2001 743 citations Masayuki Higuchi, Motoaki Seki et al. profile →
  3. Analysis of Cytokinin Mutants and Regulation of Cytokinin Metabolic Genes Reveals Important Regulatory Roles of Cytokinins in Drought, Salt and Abscisic Acid Responses, and Abscisic Acid Biosynthesis 
    2011 591 citations Rie Nishiyama, Yasuko Watanabe et al. The Plant Cell profile →
  4. In planta functions of the Arabidopsis cytokinin receptor family
    2004 550 citations Masayuki Higuchi, Ari Pekka Mähönen et al. Proceedings of the National Academy of Sciences profile →
  5. Expression of cytokinin biosynthetic isopentenyltransferase genes in Arabidopsis: tissue specificity and regulation by auxin, cytokinin, and nitrate
    2003 507 citations Kaori Miyawaki, Tatsuo Kakimoto et al. The Plant Journal profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tatsuo Kakimoto Japan 38 8.5k 7.3k 558 360 214 60 10.1k
Tomohiko Kato Japan 47 9.0k 1.1× 7.1k 1.0× 349 0.6× 388 1.1× 209 1.0× 77 10.6k
Keiko Sugimoto Japan 51 7.4k 0.9× 6.3k 0.9× 568 1.0× 322 0.9× 238 1.1× 105 8.8k
Norbert Sauer Germany 62 10.8k 1.3× 5.2k 0.7× 589 1.1× 311 0.9× 181 0.8× 142 12.2k
Sean R. Cutler United States 42 9.2k 1.1× 5.0k 0.7× 299 0.5× 298 0.8× 188 0.9× 80 10.8k
Catherine Bellini France 47 7.3k 0.9× 6.4k 0.9× 309 0.6× 257 0.7× 217 1.0× 90 9.1k
Chung‐Mo Park South Korea 57 10.3k 1.2× 7.8k 1.1× 244 0.4× 348 1.0× 293 1.4× 145 11.6k
Tina Romeis Germany 42 6.8k 0.8× 3.4k 0.5× 310 0.6× 251 0.7× 248 1.2× 64 7.8k
Anireddy S. N. Reddy United States 62 8.5k 1.0× 8.5k 1.2× 1.2k 2.1× 269 0.7× 383 1.8× 231 12.4k
Niko Geldner Switzerland 61 11.2k 1.3× 7.9k 1.1× 1.6k 2.9× 290 0.8× 127 0.6× 100 13.0k
Ranjan Swarup United Kingdom 51 10.0k 1.2× 6.8k 0.9× 270 0.5× 328 0.9× 168 0.8× 79 10.9k

Countries citing papers authored by Tatsuo Kakimoto

Since Specialization
Citations

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

Fields of papers citing papers by Tatsuo Kakimoto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tatsuo Kakimoto

This figure shows the co-authorship network connecting the top 25 collaborators of Tatsuo Kakimoto. A scholar is included among the top collaborators of Tatsuo Kakimoto 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 Tatsuo Kakimoto. Tatsuo Kakimoto 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.
Qian, Pingping, Wen Song, Guodong Wang, et al.. (2018). The CLE9/10 secretory peptide regulates stomatal and vascular development through distinct receptors. Nature Plants. 4(12). 1071–1081. 113 indexed citations
2.
Chronis, Demosthenis, Zoran S. Radaković, Shahid Siddique, et al.. (2017). Divergent expression of cytokinin biosynthesis, signaling and catabolism genes underlying differences in feeding sites induced by cyst and root‐knot nematodes. The Plant Journal. 92(2). 211–228. 36 indexed citations
3.
Kitakura, Saeko, Maciek Adamowski, Luca Santuari, et al.. (2017). BEN3/BIG2 ARF GEF is Involved in Brefeldin A-Sensitive Trafficking at the trans-Golgi Network/Early Endosome in Arabidopsis thaliana. Plant and Cell Physiology. 58(10). 1801–1811. 28 indexed citations
4.
Siddique, Shahid, Zoran S. Radaković, Demosthenis Chronis, et al.. (2015). A parasitic nematode releases cytokinin that controls cell division and orchestrates feeding site formation in host plants. Proceedings of the National Academy of Sciences. 112(41). 12669–12674. 114 indexed citations
5.
Kumari, Archana, et al.. (2014). Arabidopsis Reduces Growth Under Osmotic Stress by Decreasing SPEECHLESS Protein. Plant and Cell Physiology. 55(12). 2037–2046. 35 indexed citations
6.
Lin, Chung‐Yi, et al.. (2014). Pathways involved in vanadate‐induced root hair formation in Arabidopsis. Physiologia Plantarum. 153(1). 137–148. 17 indexed citations
7.
HARA, Toshiaki, Hirokazu Tanaka, Tatsuhiko Kondo, et al.. (2013). Differential Effects of the Peptides Stomagen, EPF1 and EPF2 on Activation of MAP Kinase MPK6 and the SPCH Protein Level. Plant and Cell Physiology. 54(8). 1253–1262. 58 indexed citations
8.
Tanaka, Hirokazu, Saeko Kitakura, Hana Rakusová, et al.. (2013). Cell Polarity and Patterning by PIN Trafficking through Early Endosomal Compartments in Arabidopsis thaliana. PLoS Genetics. 9(5). e1003540–e1003540. 69 indexed citations
9.
Uchida, Naoyuki, Jin‐Suk Lee, Robin J. Horst, et al.. (2012). Regulation of inflorescence architecture by intertissue layer ligand–receptor communication between endodermis and phloem. Proceedings of the National Academy of Sciences. 109(16). 6337–6342. 156 indexed citations
10.
Nishiyama, Rie, Yasuko Watanabe, Yasunari Fujita, et al.. (2011). Analysis of Cytokinin Mutants and Regulation of Cytokinin Metabolic Genes Reveals Important Regulatory Roles of Cytokinins in Drought, Salt and Abscisic Acid Responses, and Abscisic Acid Biosynthesis . The Plant Cell. 23(6). 2169–2183. 591 indexed citations breakdown →
11.
Kakimoto, Tatsuo, et al.. (2011). Cytokinin receptors in sporophytes are essential for male and female functions inArabidopsis thaliana. Plant Signaling & Behavior. 6(1). 66–71. 55 indexed citations
12.
13.
Peterson, Kylee M., et al.. (2009). Epidermal Cell Density is Autoregulated via a Secretory Peptide, EPIDERMAL PATTERNING FACTOR 2 in Arabidopsis Leaves. Plant and Cell Physiology. 50(6). 1019–1031. 303 indexed citations
14.
Pertry, Ine, Kateřina Václavíková, Stephen Depuydt, et al.. (2009). Identification ofRhodococcus fascianscytokinins and their modus operandi to reshape the plant. Proceedings of the National Academy of Sciences. 106(3). 929–934. 155 indexed citations
15.
Torii, Keiko U., et al.. (2007). The secretory peptide gene EPF1 enforces the stomatal one-cell-spacing rule. Genes & Development. 21(14). 1720–1725. 433 indexed citations
16.
Kondo, Tatsuhiko, Shinichiro Sawa, Atsuko Kinoshita, et al.. (2006). A Plant Peptide Encoded by CLV3 Identified by in Situ MALDI-TOF MS Analysis. Science. 313(5788). 845–848. 381 indexed citations
17.
Mähönen, Ari Pekka, Masayuki Higuchi, Kirsi Törmäkangas, et al.. (2006). Cytokinins Regulate a Bidirectional Phosphorelay Network in Arabidopsis. Current Biology. 16(11). 1116–1122. 180 indexed citations
18.
Higuchi, Masayuki, Ari Pekka Mähönen, Kaori Miyawaki, et al.. (2004). In planta functions of the Arabidopsis cytokinin receptor family. Proceedings of the National Academy of Sciences. 101(23). 8821–8826. 550 indexed citations breakdown →
19.
20.
Nakamura, Ayako, Tatsuo Kakimoto, Aya Imamura, et al.. (1999). Biochemical Characterization of a Putative Cytokinin-Responsive His-kinase, CKI1, fromArabidopsis thaliana. Bioscience Biotechnology and Biochemistry. 63(9). 1627–1630. 25 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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