Ming Yan

812 total citations
33 papers, 413 citations indexed

About

Ming Yan is a scholar working on Molecular Biology, Plant Science and Cell Biology. According to data from OpenAlex, Ming Yan has authored 33 papers receiving a total of 413 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 13 papers in Plant Science and 8 papers in Cell Biology. Recurrent topics in Ming Yan's work include Genomics and Phylogenetic Studies (9 papers), Plant Pathogens and Fungal Diseases (6 papers) and Plant biochemistry and biosynthesis (5 papers). Ming Yan is often cited by papers focused on Genomics and Phylogenetic Studies (9 papers), Plant Pathogens and Fungal Diseases (6 papers) and Plant biochemistry and biosynthesis (5 papers). Ming Yan collaborates with scholars based in China, United States and Kazakhstan. Ming Yan's co-authors include Zhaohe Yuan, Xueqing Zhao, Xiaozhu Wang, Yu Ding, Yujie Zhao, Shujuan Song, Hailan Feng, Xiaoxia Zhang, Hong Qu and Nanbert Zhong and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLANT PHYSIOLOGY and Scientific Reports.

In The Last Decade

Ming Yan

29 papers receiving 405 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ming Yan China	12	319	137	69	60	42	33	413
Agula Hasi China	14	311 1.0×	364 2.7×	35 0.5×	8 0.1×	14 0.3×	38	552
Yasuko Nagai Japan	10	160 0.5×	132 1.0×	27 0.4×	22 0.4×	13 0.3×	16	369
Carlo Fasano Italy	11	289 0.9×	213 1.6×	42 0.6×		33 0.8×	15	462
Moon Young Kim South Korea	16	91 0.3×	546 4.0×	78 1.1×	2 0.0×	15 0.4×	47	721
Anke Scholz Germany	11	268 0.8×	80 0.6×	33 0.5×	2 0.0×	26 0.6×	17	395
F. Lestienne France	10	208 0.7×	46 0.3×	28 0.4×	2 0.0×	14 0.3×	24	376
Naomi J. Marty United States	7	203 0.6×	138 1.0×	21 0.3×		44 1.0×	7	327

Countries citing papers authored by Ming Yan

Since Specialization

Citations

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

Fields of papers citing papers by Ming Yan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Yan

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Yan. A scholar is included among the top collaborators of Ming Yan 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 Yan. Ming Yan 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

Yan, Ming, Shanshan Cui, Fang Li, et al.. (2025). Common bean pan-genome reveals abundant variation patterns and relationships of stress response genes and pathways. BMC Genomics. 26(1). 495–495.

Yan, Ming, et al.. (2024). Chromosome-level Genome Assembly of Theretra japonica (Lepidoptera: Sphingidae). Scientific Data. 11(1). 770–770. 1 indexed citations

Chen, Lide, Yuan Ren, Yuying Wang, et al.. (2023). Genome-Wide Identification, Characterization, and Expression Analysis of the U-Box Gene Family in Punica granatum L.. Agronomy. 13(2). 332–332. 5 indexed citations

Zhao, Yujie, Yuying Wang, Xueqing Zhao, et al.. (2022). ARF6s Identification and Function Analysis Provide Insights Into Flower Development of Punica granatum L.. Frontiers in Plant Science. 13. 833747–833747. 4 indexed citations

Zhao, Xueqing, Yu Shen, Ming Yan, & Zhaohe Yuan. (2021). Flavonoid profiles in peels and arils of pomegranate cultivars. Journal of Food Measurement & Characterization. 16(1). 880–890. 8 indexed citations

Yu, Chunmei, Ming Yan, Huizhen Dong, et al.. (2020). Maize bHLH55 functions positively in salt tolerance through modulation of AsA biosynthesis by directly regulating GDP-mannose pathway genes. Plant Science. 302. 110676–110676. 41 indexed citations

Zhao, Yujie, et al.. (2020). Genome-wide identification and expression of YABBY genes family during flower development in Punica granatum L.. Gene. 752. 144784–144784. 26 indexed citations

Zhao, Xueqing, et al.. (2019). Characterization and comparative analysis of the complete chloroplast genome sequence from Prunus avium ‘Summit’. PeerJ. 7. e8210–e8210. 12 indexed citations

Yan, Ming, et al.. (2019). The complete chloroplast genome of cultivated apple (Malus domestica Cv. ‘Yantai Fuji 8’). SHILAP Revista de lepidopterología. 4(1). 1213–1216. 10 indexed citations

10.

Yan, Ming, et al.. (2019). The complete chloroplast genome sequence of Kerria japonica (L.) DC. ‘pleniflora’ (Rosaceae). SHILAP Revista de lepidopterología. 4(2). 3723–3724.

11.

Zhao, Xueqing, Ming Yan, Yu Ding, Xuesen Chen, & Zhaohe Yuan. (2019). The complete chloroplast genome of apple rootstock ‘M9’. SHILAP Revista de lepidopterología. 4(2). 2187–2188. 1 indexed citations

12.

Wang, Xiaozhu, Yu Huang, Ming Yan, et al.. (2017). Molecular spectrum of excision repair cross-complementation group 8 gene defects in Chinese patients with Cockayne syndrome type A. Scientific Reports. 7(1). 13686–13686. 12 indexed citations

13.

Luo, Di‐Qing, Xiaozhu Wang, Yan Meng, et al.. (2014). Mandibuloacral dysplasia type A-associated progeria caused by homozygous LMNA mutation in a family from Southern China. BMC Pediatrics. 14(1). 256–256. 25 indexed citations

14.

Ju, Weina, Ming Yan, Junhua Zou, et al.. (2010). Identification of differentially expressed transcripts and translatants targeted by knock-down of endogenous PCBP1. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics. 1804(10). 1954–1964. 16 indexed citations

15.

Ju, Weina, Dan Wu, Li Wang, et al.. (2010). A two-dimensional protein fragmentation-proteomic study of neuronal ceroid lipofuscinoses: Identification and characterization of differentially expressed proteins. Journal of Chromatography B. 879(5-6). 304–316. 7 indexed citations

16.

Wang, Xiaozhu, Zheng Wang, Ming Yan, et al.. (2008). Similarity of DMD gene deletion and duplication in the Chinese patients compared to global populations. Behavioral and Brain Functions. 4(1). 20–20. 26 indexed citations

17.

Shen, Chen‐Yang, et al.. (2008). A novel c.545-546insG mutation in the loricrin gene correlates with a heterogeneous phenotype of loricrin keratoderma. British Journal of Dermatology. 159(3). 714–719. 10 indexed citations

18.

Han, Dong, Hua Wu, Xiaoxia Zhang, et al.. (2008). Novel EDA mutation resulting in X-linked non-syndromic hypodontia and the pattern of EDA-associated isolated tooth agenesis. European Journal of Medical Genetics. 51(6). 536–546. 76 indexed citations

19.

Song, Shujuan, Yuanzhi Zhang, Biao Chen, et al.. (2006). Mutation frequency for Charcot-Marie-Tooth disease type 1 in the Chinese population is similar to that in the global ethnic patients. Genetics in Medicine. 8(8). 532–535. 14 indexed citations

20.

Li, Ker-Chau, Ming Yan, & Shinsheng Yuan. (2002). A simple statistical model for depicting the cdc-15 synchronized yeast cell cycle-regulated gene expression data. Statistica Sinica. 141–158. 16 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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