Zongyang Wang

3.2k total citations · 1 hit paper
58 papers, 2.4k citations indexed

About

Zongyang Wang is a scholar working on Plant Science, Molecular Biology and Biomedical Engineering. According to data from OpenAlex, Zongyang Wang has authored 58 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Plant Science, 17 papers in Molecular Biology and 10 papers in Biomedical Engineering. Recurrent topics in Zongyang Wang's work include Biofuel production and bioconversion (8 papers), Plant tissue culture and regeneration (7 papers) and Rice Cultivation and Yield Improvement (5 papers). Zongyang Wang is often cited by papers focused on Biofuel production and bioconversion (8 papers), Plant tissue culture and regeneration (7 papers) and Rice Cultivation and Yield Improvement (5 papers). Zongyang Wang collaborates with scholars based in China, United States and France. Zongyang Wang's co-authors include Xiuling Cai, Meng‐Min Hong, Jiping Gao, Wei Huang, Zhonghai Ren, Dai‐Yin Chao, Legong Li, Mei‐Zhen Zhu, Sheng Luan and Hong‐Xuan Lin and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Nature Genetics.

In The Last Decade

Zongyang Wang

53 papers receiving 2.3k citations

Hit Papers

A rice quantitative trait locus for salt tolerance encode... 2005 2026 2012 2019 2005 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zongyang Wang China 15 2.0k 642 528 416 283 58 2.4k
Youliang Zheng China 42 5.7k 2.9× 1.6k 2.5× 1.3k 2.5× 324 0.8× 102 0.4× 396 6.3k
Sachiko Isobe Japan 33 2.5k 1.3× 540 0.8× 1.2k 2.3× 50 0.1× 272 1.0× 135 3.3k
Jiuran Zhao China 27 1.9k 1.0× 738 1.1× 832 1.6× 65 0.2× 52 0.2× 114 2.5k
George L. Graef United States 29 2.9k 1.5× 471 0.7× 388 0.7× 139 0.3× 62 0.2× 72 3.4k
Shaojiang Chen China 30 2.3k 1.1× 888 1.4× 1.2k 2.3× 42 0.1× 119 0.4× 89 2.7k
Xianran Li United States 25 2.1k 1.1× 1.6k 2.4× 690 1.3× 65 0.2× 62 0.2× 69 2.7k
Joy Roy India 26 1.6k 0.8× 595 0.9× 336 0.6× 169 0.4× 98 0.3× 85 2.0k
Youngwoo Nam South Korea 20 770 0.4× 187 0.3× 526 1.0× 65 0.2× 73 0.3× 95 1.5k
Jihua Tang China 27 1.9k 1.0× 962 1.5× 567 1.1× 56 0.1× 73 0.3× 153 2.3k
Guorong Zhang United States 24 1.4k 0.7× 385 0.6× 279 0.5× 83 0.2× 50 0.2× 88 1.8k

Countries citing papers authored by Zongyang Wang

Since Specialization
Citations

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

Fields of papers citing papers by Zongyang Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zongyang Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Zongyang Wang. A scholar is included among the top collaborators of Zongyang 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 Zongyang Wang. Zongyang Wang 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.
Wang, Zongyang, et al.. (2024). Regional mangrove vegetation carbon stocks predicted integrating UAV-LiDAR and satellite data. Journal of Environmental Management. 368. 122101–122101. 12 indexed citations
2.
Zhu, S. H., et al.. (2024). A fine‐grained image classification method based on information interaction. IET Image Processing. 18(14). 4852–4861.
3.
Xie, Yan‐Zhao, et al.. (2024). Estimation of Horizontal Multilayer Soil Parameters Using Bayesian Inference. IEEE Transactions on Electromagnetic Compatibility. 66(6). 2111–2122.
4.
Wang, Zongyang, Feilong Li, Feifei Wu, et al.. (2023). Environmental DNA and remote sensing datasets reveal the spatial distribution of aquatic insects in a disturbed subtropical river system. Journal of Environmental Management. 351. 119972–119972. 2 indexed citations
5.
Zhu, S. H., Yu Wang, & Zongyang Wang. (2023). A lightweight license plate detection algorithm based on deep learning. IET Image Processing. 18(2). 403–411. 8 indexed citations
6.
Jin, Bo, et al.. (2023). CASSA-MEACS: A Novel Cluster Routing Method for Livestock Sensor Networks. IEEE Systems Journal. 17(4). 6401–6412. 1 indexed citations
7.
Chen, Yuhao, et al.. (2022). Vulnerability Assessment Method for Electronic Devices Excited by Transient Electromagnetic Disturbances. IEEE Electromagnetic Compatibility Magazine. 11(4). 94–99. 1 indexed citations
8.
Wang, Zongyang, et al.. (2022). Environmental DNA metabarcoding reveals the impact of different land use on multitrophic biodiversity in riverine systems. The Science of The Total Environment. 855. 158958–158958. 33 indexed citations
10.
Wang, Zongyang, et al.. (2016). MiR-181a Targets PHLPP2 to Augment AKT Signaling and Regulate Proliferation and Apoptosis in Human Keloid Fibroblasts. Cellular Physiology and Biochemistry. 40(3-4). 796–806. 53 indexed citations
11.
Chen, Shiyan, Aimin Wang, Wei Li, Zongyang Wang, & Xiuling Cai. (2008). Establishing a Gene Trap System Mediated by T‐DNA(GUS) in Rice. Journal of Integrative Plant Biology. 50(6). 742–751. 6 indexed citations
12.
Chen, Shiyan, Zongyang Wang, & Xiuling Cai. (2007). OsRRM, a Spen-like rice gene expressed specifically in the endosperm. Cell Research. 17(8). 713–721. 15 indexed citations
13.
Li, Li, et al.. (2005). Lowering Grain Amylose Content in Backcross Offsprings of indica Rice Variety 057 by Molecular Marker-Assisted Selection. 12(3). 157–162. 7 indexed citations
14.
Li, Li, et al.. (2005). Reducing Amylose Content of Indica Rice Variety 057 by Molecular Marker-Assisted Selection. Zhongguo shuidao kexue. 1 indexed citations
15.
Zhu, Ying, Xiuling Cai, Zongyang Wang, & Meng‐Min Hong. (2003). An Interaction between a MYC Protein and an EREBP Protein Is Involved in Transcriptional Regulation of the Rice Wx Gene. Journal of Biological Chemistry. 278(48). 47803–47811. 119 indexed citations
16.
Liu, Qiaoquan, et al.. (2002). Molecular marker for screening rice cultivars with intermediate amylose content in indica. 1 indexed citations
17.
Yang, Huijun, Hui Shen, Li Chen, et al.. (2002). The OsEBP-89 gene of rice encodes a putative EREBP transcription factor and is temporally expressed in developing endosperm and intercalary meristem. Plant Molecular Biology. 50(3). 379–391. 55 indexed citations
18.
Wang, Zongyang, et al.. (1999). The evidence for the excision of Tourist-Os6 from the promoter region of the rice sbe1 gene. 25(3). 274–280. 1 indexed citations
19.
Yao, Quan‐Hong, Yanyan Xing, Zongyang Wang, et al.. (1999). Cloning and sequencing of a rice (Oryza sativa L.) RAPB cDNA using yeast one-hybrid system. Science in China Series C Life Sciences. 42(4). 354–361. 1 indexed citations
20.
Wang, Zongyang, et al.. (1992). MOLECULAR CHARACTERIZATION OF RICE Wx GENE. Science China Chemistry. 35(5). 558–565. 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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