Hanyong Yu

1.0k total citations
30 papers, 727 citations indexed

About

Hanyong Yu is a scholar working on Plant Science, Genetics and Molecular Biology. According to data from OpenAlex, Hanyong Yu has authored 30 papers receiving a total of 727 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Plant Science, 27 papers in Genetics and 4 papers in Molecular Biology. Recurrent topics in Hanyong Yu's work include Genetic Mapping and Diversity in Plants and Animals (26 papers), GABA and Rice Research (15 papers) and Rice Cultivation and Yield Improvement (15 papers). Hanyong Yu is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (26 papers), GABA and Rice Research (15 papers) and Rice Cultivation and Yield Improvement (15 papers). Hanyong Yu collaborates with scholars based in China. Hanyong Yu's co-authors include Qun Xu, Xinghua Wei, Xiaoping Yuan, Feng Yue, Yiping Wang, Yaolong Yang, Caihong Wang, Mengchen Zhang, Yiping Wang and Xiaojun Niu and has published in prestigious journals such as PLoS ONE, Frontiers in Plant Science and Planta.

In The Last Decade

Hanyong Yu

30 papers receiving 716 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hanyong Yu China 15 670 446 126 18 18 30 727
Lifeng Gao China 14 648 1.0× 275 0.6× 193 1.5× 27 1.5× 64 3.6× 25 705
Xiangchun Zhou China 13 603 0.9× 314 0.7× 182 1.4× 12 0.7× 34 1.9× 22 651
G. J. N. Rao India 14 580 0.9× 176 0.4× 132 1.0× 16 0.9× 9 0.5× 28 616
Pavla Suchánková Czechia 14 726 1.1× 166 0.4× 198 1.6× 35 1.9× 22 1.2× 17 767
B. C. Viraktamath India 13 532 0.8× 241 0.5× 132 1.0× 22 1.2× 12 0.7× 28 567
Sunil Biradar India 10 427 0.6× 171 0.4× 82 0.7× 17 0.9× 20 1.1× 12 471
K. D. Liu China 9 589 0.9× 522 1.2× 154 1.2× 26 1.4× 18 1.0× 11 679
Romain De Oliveira France 7 613 0.9× 213 0.5× 192 1.5× 22 1.2× 48 2.7× 8 669
Sang Nag Ahn China 4 715 1.1× 491 1.1× 109 0.9× 24 1.3× 26 1.4× 6 758
Junjian Ni United States 8 592 0.9× 444 1.0× 185 1.5× 20 1.1× 11 0.6× 8 699

Countries citing papers authored by Hanyong Yu

Since Specialization
Citations

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

Fields of papers citing papers by Hanyong Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hanyong Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Hanyong Yu. A scholar is included among the top collaborators of Hanyong Yu 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 Hanyong Yu. Hanyong Yu 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.
Zhang, Hongyu, et al.. (2023). Global research trends in immunotherapy for glioma: a comprehensive visualization and bibliometric analysis. Frontiers in Endocrinology. 14. 1273634–1273634. 10 indexed citations
2.
Yue, Feng, Xiaoping Yuan, Yiping Wang, et al.. (2021). Validation of a QTL for Grain Size and Weight Using an Introgression Line from a Cross between Oryza sativa and Oryza minuta. Rice. 14(1). 43–43. 12 indexed citations
3.
Xu, Xin, Junhua Ye, Yingying Yang, et al.. (2020). Genome-Wide Association Study of Rice Rooting Ability at the Seedling Stage. Rice. 13(1). 59–59. 14 indexed citations
4.
Zhang, Mengchen, Zhonghua Wei, Xiaoping Yuan, et al.. (2020). Genetic Variation Dissection of Rice Blast Resistance Using an Indica Population. Rice Science. 27(4). 255–258. 2 indexed citations
5.
Lu, Qing, Caihong Wang, Xiaojun Niu, et al.. (2019). Detecting novel loci underlying rice blast resistance by integrating a genome-wide association study and RNA sequencing. Molecular Breeding. 39(6). 13 indexed citations
6.
Niu, Xiaojun, Yaolong Yang, Wang Shan, et al.. (2018). Divergent Hd1, Ghd7, and DTH7 Alleles Control Heading Date and Yield Potential of Japonica Rice in Northeast China. Frontiers in Plant Science. 9. 35–35. 43 indexed citations
7.
Zhang, Mengchen, Jing Ye, Qun Xu, et al.. (2018). Genome-wide association study of cold tolerance of Chinese indica rice varieties at the bud burst stage. Plant Cell Reports. 37(3). 529–539. 37 indexed citations
8.
Lu, Qing, Xiaojun Niu, Mengchen Zhang, et al.. (2018). Genome-Wide Association Study of Seed Dormancy and the Genomic Consequences of Improvement Footprints in Rice (Oryza sativa L.). Frontiers in Plant Science. 8. 2213–2213. 27 indexed citations
9.
Zhang, Mengchen, Qing Lu, Wei Wu, et al.. (2017). Association Mapping Reveals Novel Genetic Loci Contributing to Flooding Tolerance during Germination in Indica Rice. Frontiers in Plant Science. 8. 678–678. 58 indexed citations
10.
Yue, Feng, Qing Lu, Rongrong Zhai, et al.. (2016). Genome wide association mapping for grain shape traits in indica rice. Planta. 244(4). 819–830. 37 indexed citations
11.
Xu, Qun, Xiaoping Yuan, Shan Wang, et al.. (2016). The genetic diversity and structure of indica rice in China as detected by single nucleotide polymorphism analysis. BMC Genetics. 17(1). 53–53. 39 indexed citations
12.
Lu, Qing, Mengchen Zhang, Xiaojun Niu, et al.. (2015). Uncovering novel loci for mesocotyl elongation and shoot length in indica rice through genome-wide association mapping. Planta. 243(3). 645–657. 51 indexed citations
13.
Lu, Qing, Mengchen Zhang, Xiaojun Niu, et al.. (2015). Genetic variation and association mapping for 12 agronomic traits in indica rice. BMC Genomics. 16(1). 1067–1067. 63 indexed citations
14.
Wang, Caihong, Xiaojiao Liu, Qun Xu, et al.. (2014). Development of Novel Microsatellite Markers for the BBCC Oryza Genome (Poaceae) Using High-Throughput Sequencing Technology. PLoS ONE. 9(3). e91826–e91826. 9 indexed citations
15.
Yu, Ping, Caihong Wang, Qun Xu, et al.. (2013). Genome-wide copy number variations in Oryza sativa L.. BMC Genomics. 14(1). 649–649. 25 indexed citations
16.
Xu, Qun, Hong Chen, Caihong Wang, et al.. (2012). Genetic Diversity and Structure of New Inbred Rice Cultivars in China. Journal of Integrative Agriculture. 11(10). 1567–1573. 8 indexed citations
17.
Yu, Ping, Qun Xu, Xiaoping Yuan, et al.. (2011). Genetic Analysis and Preliminary Mapping of Two Recessive Resistance Genes to Brown Planthopper, Nilaparvata lugens Stål in Rice. Rice Science. 18(3). 238–242. 19 indexed citations
18.
Yu, Ping, Caihong Wang, Qun Xu, et al.. (2011). Detection of copy number variations in rice using array-based comparative genomic hybridization. BMC Genomics. 12(1). 372–372. 56 indexed citations
19.
Wei, Xinghua, Xiaoping Yuan, Hanyong Yu, et al.. (2009). Temporal changes in SSR allelic diversity of major rice cultivars in China. Journal of genetics and genomics. 36(6). 363–370. 21 indexed citations
20.
Yuan, Xiaoping, Xinghua Wei, Lei Hua, et al.. (2007). A Comparative Study of SSR Diversity in Chinese Major Rice Varieties Planted in 1950s and in the Recent Ten Years (1995–2004). Rice Science. 14(2). 78–84. 11 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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