Gui‐Xian Xia

10.4k total citations · 1 hit paper
64 papers, 3.5k citations indexed

About

Gui‐Xian Xia is a scholar working on Plant Science, Molecular Biology and Cell Biology. According to data from OpenAlex, Gui‐Xian Xia has authored 64 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Plant Science, 52 papers in Molecular Biology and 3 papers in Cell Biology. Recurrent topics in Gui‐Xian Xia's work include Plant-Microbe Interactions and Immunity (16 papers), Plant Molecular Biology Research (15 papers) and Plant Reproductive Biology (14 papers). Gui‐Xian Xia is often cited by papers focused on Plant-Microbe Interactions and Immunity (16 papers), Plant Molecular Biology Research (15 papers) and Plant Reproductive Biology (14 papers). Gui‐Xian Xia collaborates with scholars based in China, United States and Czechia. Gui‐Xian Xia's co-authors include Haiyun Wang, Nam‐Hai Chua, Yan Hong, Dominique Didry, Dominique Pantaloni, Ronald Melki, Valérie Laurent, Marie-France Carlier, Jérôme Santolini and Naiqin Zhong and has published in prestigious journals such as Journal of Biological Chemistry, The Journal of Cell Biology and PLoS ONE.

In The Last Decade

Gui‐Xian Xia

63 papers receiving 3.5k citations

Hit Papers

Actin Depolymerizing Factor (ADF/Cofilin) Enhances the Ra... 1997 2026 2006 2016 1997 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gui‐Xian Xia China 32 2.2k 1.9k 1.0k 265 181 64 3.5k
Christopher J. Staiger United States 54 4.8k 2.2× 5.1k 2.7× 2.3k 2.2× 292 1.1× 159 0.9× 105 7.0k
Patrick J. Hussey United Kingdom 56 5.1k 2.3× 6.0k 3.1× 2.6k 2.5× 175 0.7× 113 0.6× 140 7.9k
Brian K. Haarer United States 22 407 0.2× 2.7k 1.4× 1.5k 1.4× 122 0.5× 257 1.4× 35 3.2k
Tijs Ketelaar Netherlands 30 2.2k 1.0× 2.1k 1.1× 869 0.8× 87 0.3× 36 0.2× 61 3.0k
Peter C. Newell United Kingdom 37 504 0.2× 1.6k 0.8× 2.2k 2.1× 137 0.5× 85 0.5× 80 3.5k
Ken Matsuoka Japan 42 3.8k 1.7× 4.2k 2.2× 1.6k 1.6× 34 0.1× 65 0.4× 111 6.8k
Byung‐Ho Kang United States 38 2.4k 1.1× 2.8k 1.5× 918 0.9× 72 0.3× 24 0.1× 100 4.5k
Kentaro Nakano Japan 26 327 0.1× 1.4k 0.8× 1.0k 1.0× 57 0.2× 189 1.0× 64 1.8k
Richard J. Cyr United States 36 2.8k 1.3× 3.0k 1.6× 1.6k 1.5× 217 0.8× 12 0.1× 67 4.1k
A.M.C. Emons Netherlands 39 3.7k 1.7× 2.9k 1.5× 907 0.9× 66 0.2× 15 0.1× 100 4.6k

Countries citing papers authored by Gui‐Xian Xia

Since Specialization
Citations

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

Fields of papers citing papers by Gui‐Xian Xia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gui‐Xian Xia. 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 Gui‐Xian Xia. The network helps show where Gui‐Xian Xia may publish in the future.

Co-authorship network of co-authors of Gui‐Xian Xia

This figure shows the co-authorship network connecting the top 25 collaborators of Gui‐Xian Xia. A scholar is included among the top collaborators of Gui‐Xian Xia 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 Gui‐Xian Xia. Gui‐Xian Xia 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.
Han, Libo, Yuanbao Li, Fuxin Wang, et al.. (2019). The Cotton Apoplastic Protein CRR1 Stabilizes Chitinase 28 to Facilitate Defense against the Fungal Pathogen Verticillium dahliae. The Plant Cell. 31(2). 520–536. 81 indexed citations
2.
Wang, Fang, Yinping Ma, Ning Liu, et al.. (2017). Ectopic expression of SsPETE2, a plastocyanin from Suaeda salsa, improves plant tolerance to oxidative stress. Plant Science. 268. 1–10. 23 indexed citations
3.
Li, Yuanbao, Libo Han, Haiyun Wang, et al.. (2016). The Thioredoxin GbNRX1 Plays a Crucial Role in Homeostasis of Apoplastic Reactive Oxygen Species in Response to Verticillium dahliae Infection in Cotton. PLANT PHYSIOLOGY. 170(4). 2392–2406. 115 indexed citations
5.
Yang, Chun-Lin, Shan Liang, Haiyun Wang, et al.. (2015). Cotton Major Latex Protein 28 Functions as a Positive Regulator of the Ethylene Responsive Factor 6 in Defense against Verticillium dahliae. Molecular Plant. 8(3). 399–411. 136 indexed citations
6.
Wang, Haiyun, Yi Yu, Yong‐Duo Sun, et al.. (2015). The RING Finger Protein NtRCP1 Is Involved in the Floral Transition in Tobacco (Nicotiana tabacum). Journal of genetics and genomics. 42(6). 311–317. 3 indexed citations
7.
Zhu, Yue, Haiyun Wang, Qingzhong Peng, et al.. (2015). Functional characterization of an anthocyanidin reductase gene from the fibers of upland cotton (Gossypium hirsutum). Planta. 241(5). 1075–1089. 21 indexed citations
8.
Luo, Xiaoli, Jiahe Wu, Yuanbao Li, et al.. (2013). Synergistic Effects of GhSOD1 and GhCAT1 Overexpression in Cotton Chloroplasts on Enhancing Tolerance to Methyl Viologen and Salt Stresses. PLoS ONE. 8(1). e54002–e54002. 63 indexed citations
10.
Zhong, Naiqin, Libo Han, Xiaohong Wu, et al.. (2012). Ectopic Expression of a Bacterium NhaD‐type Na+/H+ Antiporter Leads to Increased Tolerance to Combined Salt/Alkali Stresses. Journal of Integrative Plant Biology. 54(6). 412–421. 12 indexed citations
11.
12.
Wang, Fuxin, Chunlin Yang, Yuan Yao, et al.. (2011). Proteomic analysis of the sea‐island cotton roots infected by wilt pathogen Verticillium dahliae. PROTEOMICS. 11(22). 4296–4309. 76 indexed citations
13.
Wang, Juan, Haiyun Wang, Libo Han, et al.. (2010). Overexpression of a Profilin (GhPFN2) Promotes the Progression of Developmental Phases in Cotton Fibers. Plant and Cell Physiology. 51(8). 1276–1290. 60 indexed citations
14.
Wang, Weiquan, Yaorong Wu, Yin Li, et al.. (2009). A large insert Thellungiella halophila BIBAC library for genomics and identification of stress tolerance genes. Plant Molecular Biology. 72(1-2). 91–99. 13 indexed citations
15.
Huang, Quansheng, Haiyun Wang, Peng Gao, Guoying Wang, & Gui‐Xian Xia. (2008). Cloning and characterization of a calcium dependent protein kinase gene associated with cotton fiber development. Plant Cell Reports. 27(12). 1869–1875. 56 indexed citations
16.
Gao, Peng, Juan Wang, Haiyun Wang, et al.. (2008). Co-expression and preferential interaction between two calcineurin B-like proteins and a CBL-interacting protein kinase from cotton. Plant Physiology and Biochemistry. 46(10). 935–940. 19 indexed citations
17.
Liu, Ning, Naiqin Zhong, Guiling Wang, et al.. (2007). Cloning and functional characterization of PpDBF1 gene encoding a DRE-binding transcription factor from Physcomitrella patens. Planta. 226(4). 827–838. 82 indexed citations
18.
Yu, Yi, Haiyun Wang, Lina Liu, Zhiling Chen, & Gui‐Xian Xia. (2007). Functional identification of cytokinesis-related genes from tobacco BY-2 cells. Plant Cell Reports. 26(7). 889–894. 5 indexed citations
19.
Li, Yuanli, Jie Sun, & Gui‐Xian Xia. (2005). Cloning and characterization of a gene for an LRR receptor-like protein kinase associated with cotton fiber development. Molecular Genetics and Genomics. 273(3). 217–224. 28 indexed citations
20.
Manen, Danielle, Gui‐Xian Xia, & Lucien Caro. (1994). A louse involved in the regulation of replication in plasmid pSC 101. Molecular Microbiology. 11(5). 875–884. 18 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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