Ying‐Qiang Wen

1.3k total citations
36 papers, 928 citations indexed

About

Ying‐Qiang Wen is a scholar working on Plant Science, Molecular Biology and Cell Biology. According to data from OpenAlex, Ying‐Qiang Wen has authored 36 papers receiving a total of 928 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Plant Science, 14 papers in Molecular Biology and 12 papers in Cell Biology. Recurrent topics in Ying‐Qiang Wen's work include Plant-Microbe Interactions and Immunity (19 papers), Plant Pathogens and Fungal Diseases (12 papers) and Horticultural and Viticultural Research (11 papers). Ying‐Qiang Wen is often cited by papers focused on Plant-Microbe Interactions and Immunity (19 papers), Plant Pathogens and Fungal Diseases (12 papers) and Horticultural and Viticultural Research (11 papers). Ying‐Qiang Wen collaborates with scholars based in China, United States and Tunisia. Ying‐Qiang Wen's co-authors include Shunyuan Xiao, Yuejin Wang, Yang Hu, Wenming Wang, Robert Berkey, Yurong Gao, Fengli Zhao, Ye Guo, Yuan Cheng and Yong-Tao Han and has published in prestigious journals such as The Plant Cell, PLANT PHYSIOLOGY and The Journal of Physical Chemistry C.

In The Last Decade

Ying‐Qiang Wen

35 papers receiving 915 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ying‐Qiang Wen China 16 804 472 143 41 39 36 928
Huanhuan Yang China 19 579 0.7× 283 0.6× 88 0.6× 32 0.8× 22 0.6× 48 692
Daniela Pontiggia Italy 16 1.0k 1.3× 409 0.9× 78 0.5× 25 0.6× 45 1.2× 28 1.2k
Julien Gronnier France 15 830 1.0× 502 1.1× 64 0.4× 24 0.6× 13 0.3× 23 1.0k
Shouan Liu China 11 490 0.6× 320 0.7× 62 0.4× 56 1.4× 29 0.7× 19 662
Sujon Sarowar United States 14 800 1.0× 370 0.8× 99 0.7× 112 2.7× 12 0.3× 20 928
Carmen Ruiz‐Roldán Spain 16 673 0.8× 363 0.8× 374 2.6× 27 0.7× 32 0.8× 22 826
Fangjie Xiong China 13 675 0.8× 417 0.9× 34 0.2× 20 0.5× 27 0.7× 19 776
Adrián A. Moreno Chile 14 529 0.7× 351 0.7× 216 1.5× 21 0.5× 62 1.6× 28 797
Tanya A. Wagner United States 12 835 1.0× 421 0.9× 80 0.6× 11 0.3× 36 0.9× 20 912
Danielle M. Stevens United States 10 540 0.7× 180 0.4× 60 0.4× 28 0.7× 12 0.3× 15 640

Countries citing papers authored by Ying‐Qiang Wen

Since Specialization
Citations

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

Fields of papers citing papers by Ying‐Qiang Wen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ying‐Qiang Wen. 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 Ying‐Qiang Wen. The network helps show where Ying‐Qiang Wen may publish in the future.

Co-authorship network of co-authors of Ying‐Qiang Wen

This figure shows the co-authorship network connecting the top 25 collaborators of Ying‐Qiang Wen. A scholar is included among the top collaborators of Ying‐Qiang Wen 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 Ying‐Qiang Wen. Ying‐Qiang Wen 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.
Hu, Yang, et al.. (2024). Transcription factors VviWRKY10 and VviWRKY30 co-regulate powdery mildew resistance in grapevine. PLANT PHYSIOLOGY. 195(1). 446–461. 12 indexed citations
3.
Guo, Ye, et al.. (2024). Chimeric mutations in grapevine ENHANCED DISEASE RESISTANCE1 improve resistance to powdery mildew without growth penalty. PLANT PHYSIOLOGY. 195(3). 1995–2015. 3 indexed citations
4.
Xia, Liang, Wei Feng, Chunmei Gong, et al.. (2023). A point mutation in the gene encoding magnesium chelatase I subunit influences strawberry leaf color and metabolism. PLANT PHYSIOLOGY. 192(4). 2737–2755. 28 indexed citations
5.
Shi, Jiancheng, Li Fan, Wei Feng, et al.. (2023). Systemic Colonization of Xanthomonas fragariae Strain YL19 Causing Dry Cavity Rot of Strawberry Crown Tissue in China. Plant Disease. 107(11). 3542–3552. 2 indexed citations
6.
Feng, Wei, Liang Xia, Jiancheng Shi, et al.. (2023). Pan-Genomic Analysis Identifies the Chinese Strain as a New Subspecies of Xanthomonas fragariae. Plant Disease. 108(1). 45–49. 2 indexed citations
7.
Xia, Liang, Wei Feng, Hongliang Yang, et al.. (2023). Flagella-Driven Motility Is Critical to the Virulence of Xanthomonas fragariae in Strawberry. Plant Disease. 107(11). 3506–3516. 1 indexed citations
8.
Shi, Jiancheng, Yuan Cheng, Liang Xia, et al.. (2023). Evaluation of host resistance and susceptibility to Podosphaera aphanis NWAU1 infection in 19 strawberry varieties. Scientia Horticulturae. 315. 111977–111977. 2 indexed citations
9.
Li, Ruimin, Guan‐Yu Chen, Xinqi Wang, et al.. (2023). VqMAPK3/VqMAPK6, VqWRKY33, and VqNSTS3 constitute a regulatory node in enhancing resistance to powdery mildew in grapevine. Horticulture Research. 10(7). uhad116–uhad116. 12 indexed citations
10.
Li, Yulian, et al.. (2021). First Report of Xanthomonas fragariae Strain YL19 Causing Crown Infection Pockets in Strawberry in Liaoning Province, China. Plant Disease. 105(8). 2237–2237. 7 indexed citations
11.
Li, Shasha, Shuo Chen, Keke Liu, et al.. (2021). The co-expression of genes involved in seed coat and endosperm development promotes seed abortion in grapevine. Planta. 254(5). 87–87. 11 indexed citations
12.
Guo, Ye, Yuan Cheng, Yang Hu, et al.. (2020). CRISPR/Cas9-mediated mutagenesis of VvMLO3 results in enhanced resistance to powdery mildew in grapevine (Vitis vinifera). Horticulture Research. 7(1). 116–116. 132 indexed citations
13.
Hu, Yang, et al.. (2019). The cytological basis of powdery mildew resistance in wild Chinese Vitis species. Plant Physiology and Biochemistry. 144. 244–253. 18 indexed citations
14.
Ma, Yangyang, Wei Wei, Jie Liu, et al.. (2019). Transcription factor FvTCP9 promotes strawberry fruit ripening by regulating the biosynthesis of abscisic acid and anthocyanins. Plant Physiology and Biochemistry. 146. 374–383. 56 indexed citations
15.
Cheng, Yuan, et al.. (2017). Induction, preservation, propagation and cytological observation of pro-embryonic masses of grapevine.. Guoshu xuebao. 34(8). 968–976. 2 indexed citations
16.
Hu, Yang, Yajuan Li, Yuan Cheng, et al.. (2017). Ectopic expression of Arabidopsis broad-spectrum resistance gene RPW8.2 improves the resistance to powdery mildew in grapevine (Vitis vinifera). Plant Science. 267. 20–31. 25 indexed citations
17.
Zhang, Kai, Yong-Tao Han, Fengli Zhao, et al.. (2015). Genome-wide Identification and Expression Analysis of the CDPK Gene Family in Grape, Vitis spp. BMC Plant Biology. 15(1). 164–164. 102 indexed citations
18.
Zhao, Fengli, Yajuan Li, Yang Hu, et al.. (2015). A highly efficient grapevine mesophyll protoplast system for transient gene expression and the study of disease resistance proteins. Plant Cell Tissue and Organ Culture (PCTOC). 125(1). 43–57. 48 indexed citations
19.
20.
Wang, Wenming, Ying‐Qiang Wen, Robert Berkey, & Shunyuan Xiao. (2009). Specific Targeting of the Arabidopsis Resistance Protein RPW8.2 to the Interfacial Membrane Encasing the Fungal Haustorium Renders Broad-Spectrum Resistance to Powdery Mildew  . The Plant Cell. 21(9). 2898–2913. 149 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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