Xinhui Nie

1.9k total citations
45 papers, 844 citations indexed

About

Xinhui Nie is a scholar working on Plant Science, Molecular Biology and Endocrinology. According to data from OpenAlex, Xinhui Nie has authored 45 papers receiving a total of 844 indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Plant Science, 18 papers in Molecular Biology and 13 papers in Endocrinology. Recurrent topics in Xinhui Nie's work include Research in Cotton Cultivation (29 papers), Plant and Fungal Interactions Research (13 papers) and Plant Virus Research Studies (12 papers). Xinhui Nie is often cited by papers focused on Research in Cotton Cultivation (29 papers), Plant and Fungal Interactions Research (13 papers) and Plant Virus Research Studies (12 papers). Xinhui Nie collaborates with scholars based in China, Indonesia and United Kingdom. Xinhui Nie's co-authors include Zhongxu Lin, Xianlong Zhang, Chunyuan You, Wenxia Zhao, Chao Shen, Cong Huang, Longfu Zhu, Li Wu, Zhenyuan Pan and Zheng Qu and has published in prestigious journals such as Nucleic Acids Research, PLoS ONE and Scientific Reports.

In The Last Decade

Xinhui Nie

43 papers receiving 830 citations

Peers

Xinhui Nie

ENDOC

GENET

Richard Odongo Magwanga China

Xinwu Pei China

Vasu Kuraparthy United States

Joy Nyangasi Kirungu China

Caiping Cai China

Abdelraheem Abdelraheem United States

Quánwěi Lú China

Caixiang Wang China

J. Rodriguez United States

Richard Odongo Magwanga China

Xinhui Nie

1.1k ×1.5

527 ×2.2

50 ×0.5

ENDOC

59 ×1.0

GENET

18 ×0.5

Citations per year, relative to Xinhui Nie Xinhui Nie (= 1×) peers Richard Odongo Magwanga

Countries citing papers authored by Xinhui Nie

Since Specialization

Citations

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

Fields of papers citing papers by Xinhui Nie

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xinhui Nie

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

All Works

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20 of 20 papers shown

Han, Peng, et al.. (2025). QTL mapping associated with Verticillium wilt resistance in cotton based on MAGIC population. Journal of Cotton Research. 8(1). 4 indexed citations

Wu, Yuanlong, Jiaqi You, Zhenping Liu, et al.. (2025). GWAS and eQTL analyses reveal genetic components influencing the key fiber yield trait lint percentage in upland cotton. The Plant Journal. 121(5). e70036–e70036. 2 indexed citations

Liu, Jinshan, Xiaoyan Liu, Chunyuan You, et al.. (2024). Morphological and cytological assessments reveal pollen degradation causes pollen abortion in cotton cytoplasmic male sterility lines. Journal of Cotton Research. 7(1). 1 indexed citations

Wang, Guanying, Fuqiu Wang, Zhongping Xu, et al.. (2024). Precise fine-turning of GhTFL1 by base editing tools defines ideal cotton plant architecture. Genome biology. 25(1). 59–59. 23 indexed citations

Wang, Guanying, et al.. (2024). Progress and prospect of genome editing tools development and molecular breeding in cotton. Chinese Science Bulletin (Chinese Version). 70(16). 2495–2508.

Wang, Qiongqiong, Fuqiu Wang, Guanying Wang, et al.. (2024). Utilizing the mutant library to investigate the functional characterization of GhGLR3.4 regulating jasmonic acid to defense pest infestation. The Plant Journal. 120(6). 2889–2903. 2 indexed citations

Yu, Lu, Muna Alariqi, Baoqi Li, et al.. (2024). CRISPR/dCas13(Rx) Derived RNA N⁶‐methyladenosine (m⁶A) Dynamic Modification in Plant. Advanced Science. 11(39). e2401118–e2401118. 14 indexed citations

Han, Peng, Yuanlong Wu, Zhenyuan Pan, et al.. (2024). Identification of SSR markers linked to the abscission of cotton boll traits and mining germplasm in Cotton. Journal of Cotton Research. 7(1). 3 indexed citations

Zou, Jiawei, Amjad Hussain, Yibo Fan, et al.. (2024). Systemic evaluation of various CRISPR/Cas13 orthologs for knockdown of targeted transcripts in plants. Genome biology. 25(1). 307–307. 6 indexed citations

10.

Li, Baoqi, Mengmeng Zhang, Weinan Sun, et al.. (2023). N6‐methyladenosine RNA modification regulates cotton drought response in a Ca²⁺ and ABA‐dependent manner. Plant Biotechnology Journal. 21(6). 1270–1285. 39 indexed citations

11.

Han, Peng, Wenhong Liu, Qi Zhang, et al.. (2023). Dissection of Hyperspectral Reflectance to Estimate Photosynthetic Characteristics in Upland Cotton (Gossypium hirsutum L.) under Different Nitrogen Fertilizer Application Based on Machine Learning Algorithms. Plants. 12(3). 455–455. 5 indexed citations

12.

Alariqi, Muna, Qiongqiong Wang, Hui Xi, et al.. (2023). Cotton 4‐coumarate‐CoA ligase 3 enhanced plant resistance to Verticillium dahliae by promoting jasmonic acid signaling‐mediated vascular lignification and metabolic flux. The Plant Journal. 115(1). 190–204. 29 indexed citations

13.

Meng, Qingying, Meilin Chen, Ruiting Zhang, et al.. (2023). Genome and haplotype provide insights into the population differentiation and breeding improvement of Gossypium barbadense. Journal of Advanced Research. 54. 15–27. 8 indexed citations

14.

Han, Peng, et al.. (2022). Advances and prospects of genetic mapping of Verticillium wilt resistance in cotton. Journal of Cotton Research. 5(1). 7 indexed citations

15.

Pan, Zhenyuan, Chunyuan You, Chao Shen, et al.. (2021). Association mapping and domestication analysis to dissect genetic improvement process of upland cotton yield-related traits in China. Journal of Cotton Research. 4(1). 4 indexed citations

16.

Pan, Zhenyuan, Qingyong Yang, Zhongxu Lin, et al.. (2020). Identification of candidate genes controlling fiber quality traits in upland cotton through integration of meta-QTL, significant SNP and transcriptomic data. Journal of Cotton Research. 3(1). 9 indexed citations

17.

Luo, Xiangyin, Zhonghua Li, Zhengxiu Ye, et al.. (2020). Phosphate deficiency enhances cotton resistance to Verticillium dahliae through activating jasmonic acid biosynthesis and phenylpropanoid pathway. Plant Science. 302. 110724–110724. 44 indexed citations

18.

Liu, Feng, Lihong Ma, You‐Wu Wang, et al.. (2019). GhFAD2–3 is required for anther development in Gossypium hirsutum. BMC Plant Biology. 19(1). 22 indexed citations

19.

Nie, Xinhui, Cong Huang, Chunyuan You, et al.. (2016). Genome-wide SSR-based association mapping for fiber quality in nation-wide upland cotton inbreed cultivars in China. BMC Genomics. 17(1). 352–352. 80 indexed citations

20.

Nie, Xinhui, et al.. (2010). Study on Physiology of Drought Resistance of Atriplex canescens. Xinjiang nongye kexue. 47(1). 59–66. 1 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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