Guangxia Wu

1.1k total citations
22 papers, 525 citations indexed

About

Guangxia Wu is a scholar working on Plant Science, Molecular Biology and Biochemistry. According to data from OpenAlex, Guangxia Wu has authored 22 papers receiving a total of 525 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Plant Science, 8 papers in Molecular Biology and 4 papers in Biochemistry. Recurrent topics in Guangxia Wu's work include Plant Molecular Biology Research (8 papers), Photosynthetic Processes and Mechanisms (6 papers) and Plant Stress Responses and Tolerance (5 papers). Guangxia Wu is often cited by papers focused on Plant Molecular Biology Research (8 papers), Photosynthetic Processes and Mechanisms (6 papers) and Plant Stress Responses and Tolerance (5 papers). Guangxia Wu collaborates with scholars based in China, United States and Finland. Guangxia Wu's co-authors include Haiyang Wang, Baobao Wang, Xiaojing Ma, Yurong Xie, Hai Wang, Yang Liu, Yongping Zhao, Binbin Zhao, Catherine H. Wu and Rongxin Shen and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and PLANT PHYSIOLOGY.

In The Last Decade

Guangxia Wu

21 papers receiving 520 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Guangxia Wu China 12 423 279 65 30 25 22 525
Fabiana Csukasi Spain 11 481 1.1× 388 1.4× 59 0.9× 10 0.3× 15 0.6× 17 645
Damiano Martignago Italy 11 549 1.3× 396 1.4× 101 1.6× 17 0.6× 6 0.2× 20 651
Satomi Mori Japan 10 317 0.7× 140 0.5× 72 1.1× 16 0.5× 4 0.2× 18 423
Qian Ma China 14 381 0.9× 254 0.9× 19 0.3× 6 0.2× 23 0.9× 27 540
Xinlan Xu China 9 406 1.0× 306 1.1× 37 0.6× 17 0.6× 17 0.7× 15 522
Cui Long-Gang China 3 641 1.5× 407 1.5× 106 1.6× 16 0.5× 14 0.6× 3 726
Fenglan Zhang China 15 506 1.2× 359 1.3× 74 1.1× 9 0.3× 26 1.0× 38 651
Ya-Chen Huang Taiwan 9 404 1.0× 295 1.1× 32 0.5× 10 0.3× 3 0.1× 11 536
Chengran Wang China 9 154 0.4× 140 0.5× 41 0.6× 24 0.8× 14 0.6× 24 285
Yi Kan China 10 454 1.1× 275 1.0× 132 2.0× 16 0.5× 11 0.4× 20 619

Countries citing papers authored by Guangxia Wu

Since Specialization
Citations

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

Fields of papers citing papers by Guangxia Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guangxia Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Guangxia Wu. A scholar is included among the top collaborators of Guangxia Wu 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 Guangxia Wu. Guangxia Wu 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.
Lin, Fei, Guangxia Wu, Limiao Deng, et al.. (2025). A novel deep learning framework for identifying soybean salt stress levels using RGB leaf images. Industrial Crops and Products. 228. 120874–120874. 2 indexed citations
2.
Jia, Xiaofei, et al.. (2025). A Soybean Pod Accuracy Detection and Counting Model Based on Improved YOLOv8. Agriculture. 15(6). 617–617. 4 indexed citations
3.
Liu, Hang, Fei Liu, Limiao Deng, et al.. (2024). From Organelle Morphology to Whole-Plant Phenotyping: A Phenotypic Detection Method Based on Deep Learning. Plants. 13(9). 1177–1177.
4.
Xin, Nan, Longgang Zhao, Hongtao Shi, et al.. (2024). Precision Detection of Salt Stress in Soybean Seedlings Based on Deep Learning and Chlorophyll Fluorescence Imaging. Plants. 13(15). 2089–2089. 4 indexed citations
5.
Zheng, Zhigang, Baobao Wang, Yurong Xie, et al.. (2023). Local auxin biosynthesis regulates brace root angle and lodging resistance in maize. New Phytologist. 238(1). 142–154. 20 indexed citations
6.
7.
Zhao, Yongping, Binbin Zhao, Guangxia Wu, et al.. (2022). Creation of two hyperactive variants of phytochrome B1 for attenuating shade avoidance syndrome in maize. Journal of Integrative Agriculture. 21(5). 1253–1265. 13 indexed citations
8.
Liu, Yuting, Guangxia Wu, Yongping Zhao, et al.. (2021). DWARF53 interacts with transcription factors UB2/UB3/TSH4 to regulate maize tillering and tassel branching. PLANT PHYSIOLOGY. 187(2). 947–962. 27 indexed citations
9.
Li, Quanquan, Guangxia Wu, Yongping Zhao, et al.. (2020). CRISPR/Cas9‐mediated knockout and overexpression studies reveal a role of maize phytochrome C in regulating flowering time and plant height. Plant Biotechnology Journal. 18(12). 2520–2532. 55 indexed citations
10.
Wu, Guangxia, Yongping Zhao, Rongxin Shen, et al.. (2019). Characterization of Maize Phytochrome-Interacting Factors in Light Signaling and Photomorphogenesis. PLANT PHYSIOLOGY. 181(2). 789–803. 66 indexed citations
11.
Xie, Yurong, Yang Liu, Hai Wang, et al.. (2017). Phytochrome-interacting factors directly suppress MIR156 expression to enhance shade-avoidance syndrome in Arabidopsis. Nature Communications. 8(1). 348–348. 159 indexed citations
12.
Li, Yujuan, et al.. (2017). Investigation on interactions between bovine thrombin, aptamer and active components in Danshen by capillary zone electrophoresis. Chinese Journal of Chromatography. 35(3). 339–339. 3 indexed citations
13.
Wang, Hai, Guangxia Wu, Binbin Zhao, et al.. (2016). Regulatory modules controlling early shade avoidance response in maize seedlings. BMC Genomics. 17(1). 269–269. 43 indexed citations
14.
Wu, Guangxia, et al.. (2015). A chimeric vacuolar Na+/H+ antiporter gene evolved by DNA family shuffling confers increased salt tolerance in yeast. Journal of Biotechnology. 203. 1–8. 11 indexed citations
15.
Wu, Guangxia, et al.. (2015). Cloning and expression of a ζ-carotene desaturase gene from Lycium chinense. Journal of Genetics. 94(2). 287–294. 6 indexed citations
16.
Wu, Guangxia, Gang Wang, Jing Ji, et al.. (2014). Cloning of a cytosolic ascorbate peroxidase gene from Lycium chinense Mill. and enhanced salt tolerance by overexpressing in tobacco. Gene. 543(1). 85–92. 16 indexed citations
17.
Wu, Guangxia, Gang Wang, Jing Ji, et al.. (2014). Hydrophilic C terminus of Salicornia europaea vacuolar Na+/H+ antiporter is necessary for its function. Journal of Genetics. 93(2). 425–430. 2 indexed citations
18.
Ji, Jing, et al.. (2014). Cloning and characterization of a novel ‐carotene hydroxylase gene from Lycium barbarum and its expression in Escherichia coli. Biotechnology and Applied Biochemistry. 61(6). 637–645. 7 indexed citations
19.
Ji, Jing, et al.. (2014). Molecular cloning and characterization of a novel carotenoid cleavage dioxygenase 1 from Lycium chinense. Biotechnology and Applied Biochemistry. 62(6). 772–779. 9 indexed citations
20.
Wu, Catherine H., et al.. (1991). Propeptide-mediated regulation of procollagen synthesis in IMR-90 human lung fibroblast cell cultures. Evidence for transcriptional control.. Journal of Biological Chemistry. 266(5). 2983–2987. 43 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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