Mingliang Xu

2.9k total citations
43 papers, 2.1k citations indexed

About

Mingliang Xu is a scholar working on Plant Science, Genetics and Molecular Biology. According to data from OpenAlex, Mingliang Xu has authored 43 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Plant Science, 26 papers in Genetics and 11 papers in Molecular Biology. Recurrent topics in Mingliang Xu's work include Genetic Mapping and Diversity in Plants and Animals (25 papers), Plant Disease Resistance and Genetics (19 papers) and Wheat and Barley Genetics and Pathology (11 papers). Mingliang Xu is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (25 papers), Plant Disease Resistance and Genetics (19 papers) and Wheat and Barley Genetics and Pathology (11 papers). Mingliang Xu collaborates with scholars based in China, United States and Germany. Mingliang Xu's co-authors include Schuyler S. Korban, Qin Yang, Jianrong Ye, Saihua Chen, Yi Yang, Weiwei Shi, Dongfeng Zhang, Jianbing Yan, Qing Chao and Weiliang Zuo and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Nature Genetics.

In The Last Decade

Mingliang Xu

42 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mingliang Xu China 24 1.9k 894 576 166 123 43 2.1k
M. Sheshu Madhav India 25 1.7k 0.9× 473 0.5× 686 1.2× 162 1.0× 40 0.3× 119 2.0k
R. M. Biyashev United States 15 1.6k 0.8× 622 0.7× 315 0.5× 123 0.7× 62 0.5× 26 1.8k
Qibing Lin China 22 1.5k 0.8× 493 0.6× 787 1.4× 49 0.3× 41 0.3× 37 1.7k
Gennady I. Karlov Russia 19 1.1k 0.6× 244 0.3× 481 0.8× 35 0.2× 248 2.0× 135 1.3k
Andrew Baumgarten United States 8 2.1k 1.1× 234 0.3× 1.3k 2.3× 134 0.8× 108 0.9× 9 2.5k
Giovanni Laidò Italy 19 1.3k 0.7× 496 0.6× 344 0.6× 68 0.4× 141 1.1× 23 1.5k
Jun‐Xiang Shan China 21 2.2k 1.1× 1.0k 1.2× 957 1.7× 38 0.2× 72 0.6× 26 2.5k
Xingfang Gu China 24 1.7k 0.9× 1.1k 1.2× 867 1.5× 64 0.4× 22 0.2× 80 2.2k
V. Rani India 10 893 0.5× 130 0.1× 743 1.3× 151 0.9× 26 0.2× 13 1.1k
Xinli Sun China 15 1.9k 1.0× 975 1.1× 348 0.6× 103 0.6× 54 0.4× 35 2.1k

Countries citing papers authored by Mingliang Xu

Since Specialization
Citations

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

Fields of papers citing papers by Mingliang Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingliang Xu

This figure shows the co-authorship network connecting the top 25 collaborators of Mingliang Xu. A scholar is included among the top collaborators of Mingliang Xu 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 Mingliang Xu. Mingliang Xu 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.
Zhang, Weixiao, Feng Ni, Wei Xu, et al.. (2025). qMrdd3, a major QTL conferring durable resistance to maize rough dwarf disease. Journal of Integrative Agriculture.
2.
Guo, Chenyu, et al.. (2024). The maize ZmCPK39-ZmKnox2 module regulates plant height. aBIOTECH. 5(3). 356–361. 6 indexed citations
3.
Liu, Jianju, Hui Yu, Yuanliang Liu, et al.. (2020). Genetic dissection of grain water content and dehydration rate related to mechanical harvest in maize. BMC Plant Biology. 20(1). 118–118. 22 indexed citations
4.
Liu, Qingcai, Baoshen Liu, Yongfu Tao, et al.. (2020). A helitron-induced RabGDIα variant causes quantitative recessive resistance to maize rough dwarf disease. Nature Communications. 11(1). 495–495. 56 indexed citations
5.
Zhang, Zhihai, Xuan Zhang, Zhelong Lin, et al.. (2018). The genetic architecture of nodal root number in maize. The Plant Journal. 93(6). 1032–1044. 55 indexed citations
6.
Liu, Qingqing, Huanhuan Liu, Yongfu Tao, et al.. (2017). An Atypical Thioredoxin Imparts Early Resistance to Sugarcane Mosaic Virus in Maize. Molecular Plant. 10(3). 483–497. 79 indexed citations
7.
Zuo, Weiliang, Qing Chao, Nan Zhang, et al.. (2014). A maize wall-associated kinase confers quantitative resistance to head smut. Nature Genetics. 47(2). 151–157. 280 indexed citations
8.
Xu, Ling, Yan Zhang, Wei Chen, et al.. (2014). High-resolution mapping and characterization of qRgls2, a major quantitative trait locus involved in maize resistance to gray leaf spot. BMC Plant Biology. 14(1). 230–230. 29 indexed citations
9.
Zhao, Panfeng, Guobin Zhang, Xiaojun Wu, et al.. (2013). Fine Mapping of RppP25, a Southern Rust Resistance Gene in Maize. Journal of Integrative Plant Biology. 55(5). 462–472. 22 indexed citations
10.
Xu, Mingliang. (2013). Research Progress on Maize Rough Dwarf Disease. Yumi kexue. 9 indexed citations
11.
Hou, Jing, et al.. (2013). Identification of quantitative trait loci for resistance to Curvularia leaf spot of maize. Maydica. 58. 266–273. 5 indexed citations
12.
Yang, Qin, Dongfeng Zhang, & Mingliang Xu. (2012). A Sequential Quantitative Trait Locus Fine‐Mapping Strategy Using Recombinant‐Derived ProgenyF. Journal of Integrative Plant Biology. 54(4). 228–237. 59 indexed citations
13.
Zhang, Dongfeng, Yongjie Liu, Yanling Guo, et al.. (2011). Fine-mapping of qRfg2, a QTL for resistance to Gibberella stalk rot in maize. Theoretical and Applied Genetics. 124(3). 585–596. 45 indexed citations
14.
Dionisio, Giuseppe, Hans‐Peter Piepho, Mingliang Xu, et al.. (2009). Validation of candidate genes putatively associated with resistance to SCMV and MDMV in maize (Zea mays L.) by expression profiling. BMC Plant Biology. 9(1). 15–15. 54 indexed citations
15.
Chen, Jiongjiong, Jihua Ding, Yidan Ouyang, et al.. (2008). A triallelic system of S5 is a major regulator of the reproductive barrier and compatibility of indica–japonica hybrids in rice. Proceedings of the National Academy of Sciences. 105(32). 11436–11441. 232 indexed citations
16.
Malnoy, Mickaël, Mingliang Xu, E.E. Borejsza-Wysocka, Schuyler S. Korban, & Herb S. Aldwinckle. (2008). Two Receptor-Like Genes, Vfa1 and Vfa2, Confer Resistance to the Fungal Pathogen Venturia inaequalis Inciting Apple Scab Disease. Molecular Plant-Microbe Interactions. 21(4). 448–458. 59 indexed citations
17.
Xu, Mingliang & Schuyler S. Korban. (2004). Somatic variation plays a key role in the evolution of the Vf gene family residing in the Vf locus that confers resistance to apple scab disease. Molecular Phylogenetics and Evolution. 32(1). 57–65. 19 indexed citations
18.
Xu, Mingliang, et al.. (2003). AFLP analysis of genetic variability in New Guinea impatiens. Theoretical and Applied Genetics. 106(8). 1509–1516. 25 indexed citations
19.
Li, Xiangqian, Mingliang Xu, & Schuyler S. Korban. (2002). DNA methylation profiles differ between field- andin vitro-grown leaves of apple. Journal of Plant Physiology. 159(11). 1229–1234. 46 indexed citations
20.

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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