Shuansuo Wang

2.2k total citations · 4 hit papers
9 papers, 1.6k citations indexed

About

Shuansuo Wang is a scholar working on Plant Science, Molecular Biology and Genetics. According to data from OpenAlex, Shuansuo Wang has authored 9 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Plant Science, 5 papers in Molecular Biology and 5 papers in Genetics. Recurrent topics in Shuansuo Wang's work include Plant Molecular Biology Research (7 papers), Genetic Mapping and Diversity in Plants and Animals (5 papers) and Ubiquitin and proteasome pathways (4 papers). Shuansuo Wang is often cited by papers focused on Plant Molecular Biology Research (7 papers), Genetic Mapping and Diversity in Plants and Animals (5 papers) and Ubiquitin and proteasome pathways (4 papers). Shuansuo Wang collaborates with scholars based in China and United Kingdom. Shuansuo Wang's co-authors include Xiangdong Fu, Kun Wu, Qian Liu, Jianqing Zhang, Shan Li, Yafeng Ye, Yi Wang, Xiangbin Chen, Caixia Gao and Yi Zhang and has published in prestigious journals such as Science, Nature Communications and Nature Genetics.

In The Last Decade

Shuansuo Wang

8 papers receiving 1.6k citations

Hit Papers

The OsSPL16-GW7 regulatory module determines grain shape ... 2014 2026 2018 2022 2015 2014 2020 2018 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shuansuo Wang China 8 1.5k 774 405 88 51 9 1.6k
Xianzhong Huang China 16 1.6k 1.1× 644 0.8× 677 1.7× 86 1.0× 27 0.5× 51 1.8k
Shouyun Cao China 16 1.7k 1.1× 266 0.3× 806 2.0× 64 0.7× 21 0.4× 23 1.8k
Mitsuhiro Obara Japan 20 1.4k 0.9× 297 0.4× 294 0.7× 157 1.8× 14 0.3× 47 1.4k
Banpu Ruan China 19 973 0.6× 297 0.4× 292 0.7× 42 0.5× 53 1.0× 43 1.1k
Zhongze Piao China 11 861 0.6× 205 0.3× 141 0.3× 79 0.9× 100 2.0× 30 952
Mary Beatty United States 22 1.3k 0.9× 383 0.5× 822 2.0× 108 1.2× 90 1.8× 35 1.7k
Rumei Chen China 18 1.0k 0.7× 140 0.2× 435 1.1× 43 0.5× 92 1.8× 51 1.2k
Xingming Hu China 14 1.2k 0.8× 466 0.6× 556 1.4× 47 0.5× 37 0.7× 25 1.4k
Ye‐Yang Fan China 20 1.5k 1.0× 961 1.2× 352 0.9× 74 0.8× 64 1.3× 78 1.7k

Countries citing papers authored by Shuansuo Wang

Since Specialization
Citations

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

Fields of papers citing papers by Shuansuo Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuansuo Wang

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

All Works

9 of 9 papers shown
1.
Chen, Jia, Hongbo Song, Chenyang Xu, Pengfei Wang, & Shuansuo Wang. (2025). The RING-domain E3 ubiquitin ligase OsRGLG6 regulates rice grain number and yield via ubiquitination-mediated degradation of OsOTUB1. aBIOTECH. 6(4). 774–789.
2.
Lu, Lining, Shuansuo Wang, Lijun Zhang, et al.. (2022). Met1-specific motifs conserved in OTUB subfamily of green plants enable rice OTUB1 to hydrolyse Met1 ubiquitin chains. Nature Communications. 13(1). 4672–4672. 59 indexed citations
3.
Wu, Kun, Shuansuo Wang, Wenzhen Song, et al.. (2020). Enhanced sustainable green revolution yield via nitrogen-responsive chromatin modulation in rice. Science. 367(6478). 313 indexed citations breakdown →
4.
Zhu, Liya, Han Cheng, Shuansuo Wang, et al.. (2020). Ubiquitinome Profiling Reveals the Landscape of Ubiquitination Regulation in Rice Young Panicles. Genomics Proteomics & Bioinformatics. 18(3). 305–320. 21 indexed citations
5.
Liu, Qian, Ruixi Han, Kun Wu, et al.. (2018). G-protein βγ subunits determine grain size through interaction with MADS-domain transcription factors in rice. Nature Communications. 9(1). 852–852. 255 indexed citations breakdown →
6.
Wang, Shuansuo, Kun Wu, Qian Qian, et al.. (2017). Non-canonical regulation of SPL transcription factors by a human OTUB1-like deubiquitinase defines a new plant type rice associated with higher grain yield. Cell Research. 27(9). 1142–1156. 115 indexed citations
7.
Wang, Shaokui, Shan Li, Qian Liu, et al.. (2015). The OsSPL16-GW7 regulatory module determines grain shape and simultaneously improves rice yield and grain quality. Nature Genetics. 47(8). 949–954. 525 indexed citations breakdown →
8.
Zhao, Meng, Binmei Liu, Kun Wu, et al.. (2015). Regulation of OsmiR156h through Alternative Polyadenylation Improves Grain Yield in Rice. PLoS ONE. 10(5). e0126154–e0126154. 27 indexed citations
9.
Sun, Hongying, Qian Qian, Kun Wu, et al.. (2014). Heterotrimeric G proteins regulate nitrogen-use efficiency in rice. Nature Genetics. 46(6). 652–656. 331 indexed citations breakdown →

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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