Daisuke Fujita

8.0k total citations · 1 hit paper
100 papers, 4.8k citations indexed

About

Daisuke Fujita is a scholar working on Plant Science, Genetics and Rheumatology. According to data from OpenAlex, Daisuke Fujita has authored 100 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Plant Science, 37 papers in Genetics and 12 papers in Rheumatology. Recurrent topics in Daisuke Fujita's work include Genetic Mapping and Diversity in Plants and Animals (33 papers), Rice Cultivation and Yield Improvement (30 papers) and GABA and Rice Research (21 papers). Daisuke Fujita is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (33 papers), Rice Cultivation and Yield Improvement (30 papers) and GABA and Rice Research (21 papers). Daisuke Fujita collaborates with scholars based in Japan, Philippines and Vietnam. Daisuke Fujita's co-authors include N. Kobayashi, Muhammad Farooq, Abdul Wahid, Shahzad Maqsood Ahmed Basra, Nobuya Kobayashi, Finbarr G. Horgan, Ajay Kohli, Hideshi Yasui, Yoshimichi Fukuta and Atsushi Yoshimura and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and SHILAP Revista de lepidopterología.

In The Last Decade

Daisuke Fujita

96 papers receiving 4.6k citations

Hit Papers

Plant drought stress: effects, mechanisms and management 2008 2026 2014 2020 2008 500 1000 1.5k 2.0k 2.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daisuke Fujita Japan 25 3.8k 790 628 506 349 100 4.8k
Carlos Alberto Martínez Brazil 34 2.8k 0.7× 1.1k 1.5× 310 0.5× 380 0.8× 410 1.2× 183 5.6k
Chao Wu China 36 3.8k 1.0× 1.6k 2.1× 394 0.6× 492 1.0× 381 1.1× 124 5.8k
Ivan Baxter United States 40 4.9k 1.3× 1.4k 1.8× 733 1.2× 265 0.5× 165 0.5× 81 6.0k
Patrick M. Finnegan Australia 40 3.5k 0.9× 1.6k 2.0× 164 0.3× 253 0.5× 603 1.7× 128 5.6k
Rupesh Deshmukh India 50 6.5k 1.7× 1.6k 2.1× 442 0.7× 176 0.3× 148 0.4× 190 7.4k
J. C. O’Toole Philippines 39 3.9k 1.0× 485 0.6× 681 1.1× 625 1.2× 571 1.6× 92 4.6k
Lei Shi China 40 3.5k 0.9× 1.5k 1.9× 383 0.6× 237 0.5× 404 1.2× 204 4.7k
Hong Yang China 30 1.4k 0.4× 841 1.1× 153 0.2× 256 0.5× 158 0.5× 118 2.8k
Shuyu Liu United States 28 1.7k 0.5× 252 0.3× 469 0.7× 272 0.5× 132 0.4× 128 2.4k
Marcin Rapacz Poland 31 2.4k 0.6× 1.4k 1.8× 223 0.4× 386 0.8× 70 0.2× 119 3.4k

Countries citing papers authored by Daisuke Fujita

Since Specialization
Citations

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

Fields of papers citing papers by Daisuke Fujita

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daisuke Fujita

This figure shows the co-authorship network connecting the top 25 collaborators of Daisuke Fujita. A scholar is included among the top collaborators of Daisuke Fujita 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 Daisuke Fujita. Daisuke Fujita 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
2.
Kanamori, Hiroyuki, Jian Wu, Takashi Matsumoto, et al.. (2024). Resistance haplotypes to green rice leafhopper (<i>Nephotettix cincticeps</i> Uhler) estimated in genome-wide association study in Myanmar <i>indica</i> rice landraces. Breeding Science. 74(4). 366–381. 1 indexed citations
3.
Hayashi, Masami, et al.. (2022). miR-515-5p suppresses trophoblast cell invasion and proliferation through XIAP regulation in preeclampsia. Molecular and Cellular Endocrinology. 559. 111779–111779. 10 indexed citations
4.
Yamagata, Yoshiyuki, et al.. (2021). Substitution Mapping of a Locus Responsible for Hybrid Breakdown in Populations Derived From Interspecific Introgression Line. Frontiers in Plant Science. 12. 633247–633247. 2 indexed citations
5.
Hiramatsu, Y, Takuya Kotani, Eri Nakamura, et al.. (2021). Pre-pregnancy serum complement C3 level is a predictor of preterm birth for pregnancies with systemic lupus erythematosus. Arthritis Research & Therapy. 23(1). 140–140. 10 indexed citations
6.
Sanada‐Morimura, Sachiyo, Masaya Matsumura, P. S. Virk, et al.. (2019). The Development and Characterization of Near-Isogenic and Pyramided Lines Carrying Resistance Genes to Brown Planthopper with the Genetic Background of Japonica Rice (Oryza sativa L.). Plants. 8(11). 498–498. 22 indexed citations
7.
Fujita, Daisuke, et al.. (2019). Genotypic Variation of Sensitivities to Photoperiod and Temperature in Different Growth Stages in Soybean World Mini-Core Collections (GmWMC). Tropical agriculture and development. 63(2). 69–78. 1 indexed citations
8.
Takai, Toshiyuki, Daisuke Fujita, Kazuhiro Sasaki, et al.. (2019). SPIKE, a quantitative-trait locus, increases rice grain yield under low-yield conditions. Euphytica. 215(6). 4 indexed citations
11.
Sasaki, Kazuhiro, Daisuke Fujita, Yohei Koide, et al.. (2017). Fine mapping of a quantitative trait locus for spikelet number per panicle in a new plant type rice and evaluation of a near-isogenic line for grain productivity. Journal of Experimental Botany. 68(11). 2693–2702. 16 indexed citations
12.
Hirabayashi, Hideyuki, Kazuhiro Sasaki, Ritchel B. Gannaban, et al.. (2014). qEMF3, a novel QTL for the early-morning flowering trait from wild rice, Oryza officinalis, to mitigate heat stress damage at flowering in rice, O. sativa. Journal of Experimental Botany. 66(5). 1227–1236. 108 indexed citations
13.
Moriwaki, Shinichi, Yoshiki Yamashita, Sachiko Nakamura, et al.. (2011). Prenatal diagnosis of xeroderma pigmentosum group A in Japan. The Journal of Dermatology. 39(6). 516–519. 7 indexed citations
14.
Fujita, Daisuke, et al.. (2011). Mapping and pyramiding of two major genes for resistance to the brown planthopper (Nilaparvata lugens [Stål]) in the rice cultivar ADR52. Theoretical and Applied Genetics. 124(3). 495–504. 77 indexed citations
16.
Farooq, Muhammad, et al.. (2010). Quantitative Trait Loci Mapping for Leaf Length and Leaf Width in Rice cv. IR64 Derived Lines. Journal of Integrative Plant Biology. 52(6). 578–584. 30 indexed citations
17.
Abe, Masato, Daisuke Fujita, Takaaki Nishi­oka, et al.. (2004). Synthesis and Inhibitory Action of Novel Acetogenin Mimics with Bovine Heart Mitochondrial Complex I. Biochemistry. 43(12). 3651–3658. 24 indexed citations
18.
Goji, Junko, et al.. (2003). Effect of Painting Work on Alcoholic Liver Dysfunction.. SANGYO EISEIGAKU ZASSHI. 45(6). 215–221. 2 indexed citations
19.
Shinjyo, Noriko, Daisuke Fujita, Hideto Miyoshi, et al.. (2003). Complementation of Escherichia coli ubiF mutation by Caenorhabditis elegans CLK‐1, a product of the longevity gene of the nematode worm. FEBS Letters. 543(1-3). 174–178. 7 indexed citations
20.
Koizumi, Naoko, et al.. (1989). Relationship of cadmium accumulation to zinc or copper concentration in horse liver and kidney. Environmental Research. 49(1). 104–114. 19 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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