Xiaoyu Ji

985 total citations
24 papers, 739 citations indexed

About

Xiaoyu Ji is a scholar working on Plant Science, Molecular Biology and Immunology. According to data from OpenAlex, Xiaoyu Ji has authored 24 papers receiving a total of 739 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Plant Science, 13 papers in Molecular Biology and 4 papers in Immunology. Recurrent topics in Xiaoyu Ji's work include Plant Molecular Biology Research (13 papers), Plant Stress Responses and Tolerance (11 papers) and Plant Gene Expression Analysis (6 papers). Xiaoyu Ji is often cited by papers focused on Plant Molecular Biology Research (13 papers), Plant Stress Responses and Tolerance (11 papers) and Plant Gene Expression Analysis (6 papers). Xiaoyu Ji collaborates with scholars based in China, Hong Kong and Moldova. Xiaoyu Ji's co-authors include Yucheng Wang, Xianguang Nie, Linsheng Huo, Yujia Liu, Lei Zheng, Huimin Zhao, Dandan Zang, Lei Zheng, Yujia Liu and Chao Wang and has published in prestigious journals such as PLANT PHYSIOLOGY, New Phytologist and International Journal of Molecular Sciences.

In The Last Decade

Xiaoyu Ji

23 papers receiving 731 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiaoyu Ji China 12 544 442 30 23 19 24 739
Céline Davoine France 14 541 1.0× 421 1.0× 19 0.6× 56 2.4× 12 0.6× 18 826
Jitka Široká Czechia 13 459 0.8× 319 0.7× 33 1.1× 9 0.4× 8 0.4× 28 746
Seung Hee Choi South Korea 15 830 1.5× 824 1.9× 33 1.1× 8 0.3× 21 1.1× 41 1.2k
Cunwu Chen China 12 215 0.4× 298 0.7× 27 0.9× 22 1.0× 15 0.8× 50 535
Chunxia Wu China 10 409 0.8× 196 0.4× 10 0.3× 8 0.3× 10 0.5× 18 526
Xusheng Zhao China 12 219 0.4× 247 0.6× 13 0.4× 30 1.3× 5 0.3× 45 499
Shuxia Li China 21 678 1.2× 519 1.2× 18 0.6× 8 0.3× 15 0.8× 59 1.0k
Ravi Kumar India 15 455 0.8× 640 1.4× 44 1.5× 11 0.5× 16 0.8× 26 904

Countries citing papers authored by Xiaoyu Ji

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoyu Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaoyu Ji

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoyu Ji. A scholar is included among the top collaborators of Xiaoyu Ji 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 Xiaoyu Ji. Xiaoyu Ji 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.
2.
Zhang, Zerui, Yijun Wang, Siwen Li, et al.. (2024). Transcription factor ELF4 in physiology and diseases: Molecular roles and clinical implications. Genes & Diseases. 12(3). 101394–101394. 2 indexed citations
3.
Wang, Lei, Lei Wang, Benzhe Zhou, et al.. (2023). Investigation of the effect of non-uniform stress distribution on the transient electromagnetic behavior of a no-insulation REBCO racetrack coil. Physica C Superconductivity. 617. 1354403–1354403. 7 indexed citations
4.
Wu, Kemin, et al.. (2022). Evaluation of a Reliable Biomarker in a Cecal Ligation and Puncture-Induced Mouse Model of Sepsis. Journal of Visualized Experiments. 1 indexed citations
5.
Li, Dan, et al.. (2022). 2,3,5,4′-tetrahydroxystilbene-2-O-β-D-glucopyranoside enhances the hepatotoxicity of emodin in vitro and in vivo. Toxicology Letters. 365. 74–85. 6 indexed citations
6.
Zhang, Qun, Zhibo Wang, Ruikun Huang, et al.. (2022). Genome-wide identification, expression and salt stress tolerance analysis of the GRAS transcription factor family in Betula platyphylla. Frontiers in Plant Science. 13. 1022076–1022076. 10 indexed citations
7.
Wu, Kemin, et al.. (2022). Evaluation of a Reliable Biomarker in a Cecal Ligation and Puncture-Induced Mouse Model of Sepsis. Journal of Visualized Experiments. 3 indexed citations
8.
Wang, Zhibo, et al.. (2021). Revealing the salt tolerance mechanism of Tamarix hispida by large-scale identification of genes conferring salt tolerance. Tree Physiology. 41(11). 2153–2170. 20 indexed citations
9.
Wang, Zhibo, et al.. (2021). UNFERTILIZED EMBRYO SAC 12 phosphorylation plays a crucial role in conferring salt tolerance. PLANT PHYSIOLOGY. 188(2). 1385–1401. 21 indexed citations
10.
Xu, Tao, Wei Ding, Xiaoyu Ji, et al.. (2019). Oxidative Stress in Cell Death and Cardiovascular Diseases. Oxidative Medicine and Cellular Longevity. 2019. 1–11. 93 indexed citations
11.
Li, Ziyi, Huijun Lu, Linsheng Huo, et al.. (2019). The NAC Protein from Tamarix hispida, ThNAC7, Confers Salt and Osmotic Stress Tolerance by Increasing Reactive Oxygen Species Scavenging Capability. Plants. 8(7). 221–221. 33 indexed citations
12.
Ji, Xiaoyu, Liuqiang Wang, Dandan Zang, & Yucheng Wang. (2018). Transcription Factor-Centered Yeast One-Hybrid Assay. Methods in molecular biology. 1794. 183–194. 21 indexed citations
13.
Huang, Aihua, Ruoting Zhan, Wei‐Wen Chen, et al.. (2017). Metabolic Profile of Skimmianine in Rats Determined by Ultra-Performance Liquid Chromatography Coupled with Quadrupole Time-of-Flight Tandem Mass Spectrometry. Molecules. 22(4). 489–489. 17 indexed citations
14.
Ji, Xiaoyu, Xianguang Nie, Yujia Liu, et al.. (2016). AbHLHgene fromTamarix hispidaimproves abiotic stress tolerance by enhancing osmotic potential and decreasing reactive oxygen species accumulation. Tree Physiology. 36(2). tpv139–tpv139. 45 indexed citations
15.
Liu, Yujia, Xiaoyu Ji, Xianguang Nie, et al.. (2015). Arabidopsis AtbHLH112 regulates the expression of genes involved in abiotic stress tolerance by binding to their E‐box and GCG‐box motifs. New Phytologist. 207(3). 692–709. 187 indexed citations
16.
Ji, Xiaoyu, Guifeng Liu, Yujia Liu, et al.. (2015). The regulatory network of ThbZIP1 in response to abscisic acid treatment. Frontiers in Plant Science. 6. 25–25. 8 indexed citations
17.
Zang, Dandan, Chao Wang, Xiaoyu Ji, & Yucheng Wang. (2015). Tamarix hispida zinc finger protein ThZFP1 participates in salt and osmotic stress tolerance by increasing proline content and SOD and POD activities. Plant Science. 235. 111–121. 72 indexed citations
18.
Ji, Xiaoyu, Guifeng Liu, Yujia Liu, et al.. (2013). The bZIP protein from Tamarix hispida, ThbZIP1, is ACGT elements binding factor that enhances abiotic stress signaling in transgenic Arabidopsis. BMC Plant Biology. 13(1). 151–151. 59 indexed citations
19.
Zheng, Lei, Guifeng Liu, Xiangnan Meng, et al.. (2013). A WRKY gene from Tamarix hispida, ThWRKY4, mediates abiotic stress responses by modulating reactive oxygen species and expression of stress-responsive genes. Plant Molecular Biology. 82(4-5). 303–320. 76 indexed citations
20.
Ji, Xiaoyu, Yucheng Wang, & Guifeng Liu. (2012). Expression Analysis of MYC Genes from Tamarix hispida in Response to Different Abiotic Stresses. International Journal of Molecular Sciences. 13(2). 1300–1313. 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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