Shinya Yoshida

1.4k total citations · 1 hit paper
23 papers, 962 citations indexed

About

Shinya Yoshida is a scholar working on Plant Science, Genetics and Molecular Biology. According to data from OpenAlex, Shinya Yoshida has authored 23 papers receiving a total of 962 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Plant Science, 7 papers in Genetics and 5 papers in Molecular Biology. Recurrent topics in Shinya Yoshida's work include Genetic Mapping and Diversity in Plants and Animals (7 papers), Rice Cultivation and Yield Improvement (7 papers) and Plant Disease Resistance and Genetics (6 papers). Shinya Yoshida is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (7 papers), Rice Cultivation and Yield Improvement (7 papers) and Plant Disease Resistance and Genetics (6 papers). Shinya Yoshida collaborates with scholars based in Japan, Hungary and United States. Shinya Yoshida's co-authors include Makoto Matsuoka, Hidemi Kitano, Kenji Yano, Ko Hirano, Masanori Yamasaki, Koichiro Aya, Eiji Yamamoto, Li Hu, Hideyuki Takeuchi and Chiharu Nakamura and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Genetics and Frontiers in Plant Science.

In The Last Decade

Shinya Yoshida

22 papers receiving 936 citations

Hit Papers

Genome-wide association study using whole-genome sequenci... 2016 2026 2019 2022 2016 100 200 300 400
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. Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice
    2016 461 citations Kenji Yano, Eiji Yamamoto et al. Nature Genetics profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shinya Yoshida Japan 12 822 481 166 48 36 23 962
Osamu Ideta Japan 14 714 0.9× 375 0.8× 178 1.1× 81 1.7× 25 0.7× 31 802
Xiaoding Ma China 18 910 1.1× 413 0.9× 336 2.0× 35 0.7× 23 0.6× 54 1.1k
Rajinder K. Jain India 13 747 0.9× 386 0.8× 151 0.9× 23 0.5× 22 0.6× 28 822
César Martínez Colombia 13 1.5k 1.9× 1.1k 2.2× 177 1.1× 64 1.3× 34 0.9× 29 1.6k
S. R. McCouch United States 9 1.0k 1.2× 727 1.5× 140 0.8× 18 0.4× 51 1.4× 16 1.1k
Gang‐Seob Lee South Korea 15 789 1.0× 155 0.3× 318 1.9× 48 1.0× 72 2.0× 92 919
Arnaud Bellec France 16 897 1.1× 207 0.4× 329 2.0× 32 0.7× 50 1.4× 27 992
Yongcai Fu China 16 1.1k 1.3× 668 1.4× 223 1.3× 26 0.5× 41 1.1× 33 1.1k

Countries citing papers authored by Shinya Yoshida

Since Specialization
Citations

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

Fields of papers citing papers by Shinya Yoshida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shinya Yoshida

This figure shows the co-authorship network connecting the top 25 collaborators of Shinya Yoshida. A scholar is included among the top collaborators of Shinya Yoshida 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 Shinya Yoshida. Shinya Yoshida 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.
Suganami, Mao, Hideki Yoshida, Shinya Yoshida, et al.. (2024). Redefining awn development in rice through the breeding history of Japanese awn reduction. Frontiers in Plant Science. 15. 1370956–1370956. 2 indexed citations
2.
Bamba, Shigeki, Takayuki Imai, Masaya Sasaki, et al.. (2022). Altered gut microbiota in patients with small intestinal bacterial overgrowth. Journal of Gastroenterology and Hepatology. 38(1). 61–69. 17 indexed citations
3.
Yano, Kenji, Yoichi Morinaka, Fanmiao Wang, et al.. (2019). GWAS with principal component analysis identifies a gene comprehensively controlling rice architecture. Proceedings of the National Academy of Sciences. 116(42). 21262–21267. 145 indexed citations
4.
Yoshida, Shinya, et al.. (2017). Starch Properties Affecting Maltose Production Ability in Vegetable Black Soybean Seeds (Edamame) with Different Maturation Periods. The Horticulture Journal. 87(2). 236–249. 1 indexed citations
5.
Yano, Kenji, Eiji Yamamoto, Koichiro Aya, et al.. (2016). Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice. Nature Genetics. 48(8). 927–934. 461 indexed citations breakdown →
6.
Yoshida, Shinya, et al.. (2014). Mapping QTLs for cold tolerance at germination and the early seedling stage in rice (Oryza sativaL.). Biotechnology & Biotechnological Equipment. 28(6). 989–998. 34 indexed citations
7.
Sugimoto, Takuma, Masayasu Kato, Shinya Yoshida, et al.. (2012). Pathogenic diversity of Phytophthora sojae and breeding strategies to develop Phytophthora-resistant soybeans. Breeding Science. 61(5). 511–522. 88 indexed citations
8.
Sayama, Takashi, et al.. (2012). Diversity and population structure of black soybean landraces originating from Tanba and neighboring regions. Breeding Science. 61(5). 593–601. 13 indexed citations
9.
Yoshida, Shinya. (2012). The Origin of Sake-Brewing Rice Varieties and These Genetic Backgrounds. JOURNAL OF THE BREWING SOCIETY OF JAPAN. 107(10). 710–718. 4 indexed citations
10.
Mori, Naoki, et al.. (2012). Induction and Repression of Gene Expression Mediating Ethylene Biosynthesis and Sodium/Proton Exchange in Rice Seedlings Under Submergence Stress. Biotechnology & Biotechnological Equipment. 26(3). 2945–2951. 2 indexed citations
11.
Sugimoto, Takuma, et al.. (2009). The Effect of Potassium Nitrate on the Reduction of Phytophthora Stem Rot Disease of Soybeans, the Growth Rate and Zoospore Release of Phytophthora sojae. Journal of Phytopathology. 157(6). 379–389. 13 indexed citations
12.
Yoshida, Shinya, et al.. (2008). Sequence diversity and copy number variation of Mutator-like transposases in wheat. Genetics and Molecular Biology. 31(2). 539–546. 1 indexed citations
13.
14.
Sugimoto, Takuma, et al.. (2006). Race distribution of Phytophthora sojae on soybean in Hyogo, Japan. Journal of General Plant Pathology. 72(2). 92–97. 18 indexed citations
15.
Yoshida, Shinya, et al.. (2004). A Maize MuDR-Like Element Expressed in Rice Callus Subcultured with Proline. Hereditas. 129(1). 95–99. 6 indexed citations
16.
17.
Yoshida, Shinya, et al.. (2002). QTL Analysis for Plant and Grain Characters of Sake-brewing Rice Using a Doubled Haploid Population.. Breeding Science. 52(4). 309–317. 76 indexed citations
18.
Yoshida, Shinya, et al.. (1999). Proline Stimulates Albino Regeneration from Anther- and Seed-derived Rice Callus under High Osmosis. Journal of Plant Physiology. 155(1). 107–109. 4 indexed citations
19.
20.
Yoshida, Shinya, et al.. (1990). Application of anther culture to rice breeding. II. Varietal difference in regeneration ability and effect of BA in callus formation medium.. 13–16. 2 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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