Ming Wang

9.3k total citations · 5 hit papers
103 papers, 6.0k citations indexed

About

Ming Wang is a scholar working on Plant Science, Molecular Biology and Animal Science and Zoology. According to data from OpenAlex, Ming Wang has authored 103 papers receiving a total of 6.0k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Plant Science, 42 papers in Molecular Biology and 12 papers in Animal Science and Zoology. Recurrent topics in Ming Wang's work include Plant Molecular Biology Research (26 papers), Plant nutrient uptake and metabolism (16 papers) and Plant Virus Research Studies (10 papers). Ming Wang is often cited by papers focused on Plant Molecular Biology Research (26 papers), Plant nutrient uptake and metabolism (16 papers) and Plant Virus Research Studies (10 papers). Ming Wang collaborates with scholars based in China, United States and Spain. Ming Wang's co-authors include Hailing Jin, Arne Weiberg, Hsien‐Da Huang, Feng-Mao Lin, Isgouhi Kaloshian, Zhihong Zhang, Hongwei Zhao, Kwok‐Yung Yuen, Patrick C. Y. Woo and Susanna K. P. Lau and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Ming Wang

98 papers receiving 5.9k citations

Hit Papers

Discovery of Seven Novel Mammalian and Avian Coronaviruse... 2012 2026 2016 2021 2012 2013 2018 2016 2019 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming Wang China 26 3.0k 2.1k 1.5k 975 486 103 6.0k
Jianfa Bai United States 35 1.8k 0.6× 921 0.4× 1.1k 0.8× 649 0.7× 597 1.2× 143 4.4k
John Huddleston United States 25 1.6k 0.5× 4.4k 2.1× 2.2k 1.5× 370 0.4× 298 0.6× 40 7.8k
Lei Zhou China 43 1.2k 0.4× 1.6k 0.8× 2.6k 1.8× 2.8k 2.8× 152 0.3× 219 6.2k
Maja Ravnikar Slovenia 42 3.3k 1.1× 1.3k 0.6× 570 0.4× 204 0.2× 722 1.5× 210 5.3k
Chan Ding China 40 317 0.1× 2.3k 1.1× 1.3k 0.9× 1.3k 1.4× 504 1.0× 306 6.9k
Seán Doyle Ireland 40 901 0.3× 1.6k 0.8× 1.2k 0.8× 473 0.5× 97 0.2× 130 4.5k
Abdul Rahman Omar Malaysia 41 567 0.2× 1.6k 0.8× 1.4k 1.0× 1.7k 1.7× 79 0.2× 321 6.0k
Weihuan Fang China 37 293 0.1× 1.4k 0.7× 805 0.5× 866 0.9× 538 1.1× 210 4.6k
Sang‐Won Lee South Korea 27 1.0k 0.3× 678 0.3× 580 0.4× 405 0.4× 181 0.4× 203 3.0k
Thomas D. Otto United Kingdom 45 1.1k 0.4× 4.1k 2.0× 927 0.6× 126 0.1× 377 0.8× 122 8.9k

Countries citing papers authored by Ming Wang

Since Specialization
Citations

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

Fields of papers citing papers by Ming Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Wang. A scholar is included among the top collaborators of Ming Wang 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 Ming Wang. Ming Wang 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.
Wang, Ming, Yan He, Zhenhui Zhong, et al.. (2025). Histone H3 lysine 4 methylation recruits DNA demethylases to enforce gene expression in Arabidopsis. Nature Plants. 11(2). 206–217. 9 indexed citations
2.
Wang, Ming, Nana Wang, Jing Yuan, et al.. (2024). Removal of chromate in aqueous solutions by termite nests and reduction chromate accumulation in Brassica chinensis L.. Frontiers in Sustainable Food Systems. 8.
3.
Wang, Junli, Ming Wang, Li Zhang, et al.. (2024). WAV E3 ubiquitin ligases mediate degradation of IAA32/34 in the TMK1-mediated auxin signaling pathway during apical hook development. Proceedings of the National Academy of Sciences. 121(17). e2314353121–e2314353121. 15 indexed citations
4.
Wang, Ming, Meng Sun, Qiuhua Li, et al.. (2024). ZmNAC17 Regulates Mesocotyl Elongation by Mediating Auxin and ROS Biosynthetic Pathways in Maize. International Journal of Molecular Sciences. 25(9). 4585–4585. 3 indexed citations
5.
Wang, Shuya, Ming Wang, Zhenhui Zhong, et al.. (2024). MBD2 couples DNA methylation to transposable element silencing during male gametogenesis. Nature Plants. 10(1). 13–24. 13 indexed citations
6.
Liu, Chenyang, et al.. (2024). Pecan-medicinal crops intercropping improved soil fertility and promoted interactions between soil microorganisms and metabolites. Chemical and Biological Technologies in Agriculture. 11(1). 1 indexed citations
7.
Jablonski, Becca B.R., et al.. (2023). Producers marketing a novel crop: a field-level view of hemp market channels. Renewable Agriculture and Food Systems. 38. 2 indexed citations
8.
Li, Zheng, Ming Wang, Zhenhui Zhong, et al.. (2023). The MOM1 complex recruits the RdDM machinery via MORC6 to establish de novo DNA methylation. Nature Communications. 14(1). 4135–4135. 15 indexed citations
9.
Wang, Ming, Zhenhui Zhong, Javier Gallego‐Bartolomé, et al.. (2023). A gene silencing screen uncovers diverse tools for targeted gene repression in Arabidopsis. Nature Plants. 9(3). 460–472. 27 indexed citations
10.
Wang, Ming, Zhenhui Zhong, Javier Gallego‐Bartolomé, et al.. (2023). Arabidopsis TRB proteins function in H3K4me3 demethylation by recruiting JMJ14. Nature Communications. 14(1). 1736–1736. 24 indexed citations
12.
Gardiner, Jason, Basudev Ghoshal, Ming Wang, & Steven E. Jacobsen. (2022). CRISPR–Cas-mediated transcriptional control and epi-mutagenesis. PLANT PHYSIOLOGY. 188(4). 1811–1824. 29 indexed citations
13.
Liu, Wanlu, Javier Gallego‐Bartolomé, Yuxing Zhou, et al.. (2021). Ectopic targeting of CG DNA methylation in Arabidopsis with the bacterial SssI methyltransferase. Nature Communications. 12(1). 3130–3130. 33 indexed citations
14.
Xue, Yan, Zhenhui Zhong, C. Jake Harris, et al.. (2021). Arabidopsis MORC proteins function in the efficient establishment of RNA directed DNA methylation. Nature Communications. 12(1). 4292–4292. 34 indexed citations
15.
Cai, Qiang, Lulu Qiao, Ming Wang, et al.. (2018). Plants send small RNAs in extracellular vesicles to fungal pathogen to silence virulence genes. Science. 360(6393). 1126–1129. 809 indexed citations breakdown →
16.
Xie, Chaojun, Wenzhe Su, Kuibiao Li, et al.. (2016). [Effect of supply of fresh poultry products on reducing environment contamination of avian influenza virus in markets].. PubMed. 37(3). 353–7. 2 indexed citations
17.
Weiberg, Arne, Ming Wang, Feng-Mao Lin, et al.. (2013). Fungal Small RNAs Suppress Plant Immunity by Hijacking Host RNA Interference Pathways. Science. 342(6154). 118–123. 933 indexed citations breakdown →
18.
Zhang, Xian, et al.. (2005). Cytological studies on recessive nuclease male sterile lines in watermelon. Xibei Nong-Lin Keji Daxue xuebao. Ziran kexue ban. 3 indexed citations
19.
Zhang, Guihua, et al.. (2004). AFLP Markers of Cucumber Powdery Mildew Resistance-related Gene. Acta Horticulturae Sinica. 31(2). 189. 4 indexed citations
20.
Wang, Ming. (2001). Ultrastructure of the Mutant FBL of the Cyanobacterium Spirulina platensis. Jiguang shengwu xuebao. 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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