Hiroyoshi Iwata

9.1k total citations · 2 hit papers
193 papers, 6.0k citations indexed

About

Hiroyoshi Iwata is a scholar working on Plant Science, Genetics and Molecular Biology. According to data from OpenAlex, Hiroyoshi Iwata has authored 193 papers receiving a total of 6.0k indexed citations (citations by other indexed papers that have themselves been cited), including 138 papers in Plant Science, 118 papers in Genetics and 39 papers in Molecular Biology. Recurrent topics in Hiroyoshi Iwata's work include Genetic Mapping and Diversity in Plants and Animals (92 papers), Genetics and Plant Breeding (61 papers) and Genetic and phenotypic traits in livestock (59 papers). Hiroyoshi Iwata is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (92 papers), Genetics and Plant Breeding (61 papers) and Genetic and phenotypic traits in livestock (59 papers). Hiroyoshi Iwata collaborates with scholars based in Japan, Egypt and United States. Hiroyoshi Iwata's co-authors include Jean‐Luc Jannink, Aaron J. Lorenz, Takeshi Hayashi, Yoshihiko Tsumura, S. Ninomiya, Ryo Ohsawa, Hiromi Kajiya‐Kanegae, Akio Onogi, Kaworu Ebana and Yasushi Takano and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Genetics and Bioinformatics.

In The Last Decade

Hiroyoshi Iwata

183 papers receiving 5.8k citations

Hit Papers

align trajectories sort by overperformance

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.

Genomic selection in plant breeding: from theory to practice

2010 801 citations Hiroyoshi Iwata et al. profile →
SHAPE: A Computer Program Package for Quantitative Evaluation of Biological Shapes Based on Elliptic Fourier Descriptors

2002 619 citations Hiroyoshi Iwata profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Hiroyoshi Iwata	4.1k	3.1k	925	602	579	193	6.0k
Zhao‐Bang Zeng	5.7k 1.4×	6.5k 2.1×	1.7k 1.9×	812 1.3×	355 0.6×	90	9.3k
Rongling Wu	3.5k 0.9×	3.4k 1.1×	2.7k 3.0×	289 0.5×	190 0.3×	309	6.9k
Karin Meyer	2.2k 0.5×	6.3k 2.1×	457 0.5×	742 1.2×	264 0.5×	167	8.1k
Julin Maloof	5.8k 1.4×	1.1k 0.4×	4.1k 4.5×	517 0.9×	289 0.5×	102	7.7k
Isabel Roldán-Ruíz	3.9k 1.0×	2.1k 0.7×	1.4k 1.6×	2.1k 3.4×	827 1.4×	184	6.6k
Daniel H. Chitwood	3.3k 0.8×	368 0.1×	2.0k 2.1×	436 0.7×	238 0.4×	79	4.1k
Shizhong Xu	4.1k 1.0×	4.5k 1.5×	995 1.1×	239 0.4×	173 0.3×	181	6.5k
Nolan C. Kane	2.4k 0.6×	1.9k 0.6×	1.7k 1.9×	1.1k 1.8×	579 1.0×	114	4.8k
Peter Midford	626 0.2×	964 0.3×	2.5k 2.7×	1.1k 1.9×	887 1.5×	30	5.1k
Dorian J. Garrick	3.0k 0.7×	7.9k 2.6×	914 1.0×	219 0.4×	318 0.5×	318	10.2k

Countries citing papers authored by Hiroyoshi Iwata

Since Specialization

Citations

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

Fields of papers citing papers by Hiroyoshi Iwata

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hiroyoshi Iwata

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

All Works

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20 of 20 papers shown

Kobori, Shungo, Takumi Sato, Megumi Narukawa, et al.. (2025). I-SVVS: integrative stochastic variational variable selection to explore joint patterns of multi-omics microbiome data. Briefings in Bioinformatics. 26(3). 1 indexed citations

Araki, Atsuko, Chihiro Miyashita, Takeshi Yamaguchi, et al.. (2024). Heavy metals and trace elements in maternal blood and prevalence of congenital limb abnormalities among newborns: the Japan Environment and Children’s Study. Environmental Health and Preventive Medicine. 29(0). 36–36. 1 indexed citations

Barras, C., Yoshihiro Ohmori, Yuji Yamasaki, et al.. (2024). High-Throughput Phenotyping of Soybean Biomass: Conventional Trait Estimation and Novel Latent Feature Extraction Using UAV Remote Sensing and Deep Learning Models. Plant Phenomics. 6. 244–244. 7 indexed citations

Kaga, Akito, et al.. (2024). Cross potential selection: a proposal for optimizing crossing combinations in recurrent selection using the usefulness criterion of future inbred lines. G3 Genes Genomes Genetics. 14(11).

Miura, Naoko, et al.. (2024). Quantitative Genetic Aspects of Accuracy of Tree Biomass Measurement Using LiDAR. Remote Sensing. 16(24). 4790–4790.

Ohmori, Yoshihiro, Yuji Yamasaki, Hirokazu Takahashi, et al.. (2023). Random regression for modeling soybean plant response to irrigation changes using time-series multispectral data. Frontiers in Plant Science. 14. 1201806–1201806. 5 indexed citations

Kinoshita, S., et al.. (2023). Assessing the Potential for Genome-Assisted Breeding in Red Perilla Using Quantitative Trait Locus Analysis and Genomic Prediction. Genes. 14(12). 2137–2137.

Ohyama, Akio, Hiroshi Matsunaga, Yasushi Kawasaki, et al.. (2023). Bayesian estimation of multi-allele QTLs for agricultural traits in tomato using recombinant inbred lines derived from two F1 hybrid cultivars. Euphytica. 219(1). 2 indexed citations

Iwata, Hiroyoshi, et al.. (2023). The Clinical Utility of Relative Bradycardia for Identifying Cases of Coronavirus Disease 2019 Pneumonia: A Retrospective Pneumonia Cohort Study. Internal Medicine. 62(13). 1931–1938. 1 indexed citations

10.

Takanashi, Hideki, Hiromi Kajiya‐Kanegae, Asuka Nishimura, et al.. (2022). DOMINANT AWN INHIBITOR Encodes the ALOG Protein Originating from Gene Duplication and Inhibits AWN Elongation by Suppressing Cell Proliferation and Elongation in Sorghum. Plant and Cell Physiology. 63(7). 901–918. 17 indexed citations

11.

Kajiya‐Kanegae, Hiromi, Yoshihiro Ohmori, Yuji Yamasaki, et al.. (2022). Time‐series multispectral imaging in soybean for improving biomass and genomic prediction accuracy. The Plant Genome. 15(4). e20244–e20244. 10 indexed citations

12.

Iwata, Hiroyoshi, et al.. (2022). Development of a high-throughput field phenotyping rover optimized for size-limited breeding fields as open-source hardware. Breeding Science. 72(1). 66–74. 3 indexed citations

13.

Iwata, Hiroyoshi, Hiroyuki Shimono, Akio Kimura, et al.. (2021). A Deep Learning Method to Impute Missing Values and Compress Genome-ide Polymorphism Data in Rice.. Bioinformatics. 101–109. 2 indexed citations

14.

Iwata, Hiroyoshi, Hiroyuki Shimono, Akio Kimura, et al.. (2021). A Deep Learning Method to Impute Missing Values and Compress Genome-wide Polymorphism Data in Rice. 101–109. 2 indexed citations

15.

Yamasaki, Masanori, et al.. (2020). Predicting Rice Heading Date Using an Integrated Approach Combining a Machine Learning Method and a Crop Growth Model. Frontiers in Genetics. 11. 599510–599510. 17 indexed citations

16.

Morota, Gota, et al.. (2019). Consideration of heat stress in multiple lactation test–day models for dairy production traits. Bulletin - International Bull Evaluation Service/Interbull bulletin. 81–87. 2 indexed citations

17.

Onogi, Akio, et al.. (2018). Effect of heat stress on production traits of Holstein cattle in Japan: parameter estimation using test-day records of first parity and genome wide markers. Bulletin - International Bull Evaluation Service/Interbull bulletin. 2 indexed citations

18.

Iwata, Hiroyoshi, Mai F. Minamikawa, Hiromi Kajiya‐Kanegae, Motoyuki Ishimori, & Takeshi Hayashi. (2016). Genomics-assisted breeding in fruit trees. Breeding Science. 66(1). 100–115. 70 indexed citations

19.

Kondo, Shinya, et al.. (2013). Intra-Specific Ploidy Variations in Cultivated Chinese Yam (Dioscorea polystachya Turcz.). Tropical agriculture and development. 57(3). 101–107. 9 indexed citations

20.

Tsumura, Yoshihiko & Hiroyoshi Iwata. (2003). . Journal of the Japanese Society of Revegetation Technology. 28(4). 470–475. 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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