Jingmei Mu

785 total citations
19 papers, 481 citations indexed

About

Jingmei Mu is a scholar working on Plant Science, Genetics and Molecular Biology. According to data from OpenAlex, Jingmei Mu has authored 19 papers receiving a total of 481 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Plant Science, 11 papers in Genetics and 1 paper in Molecular Biology. Recurrent topics in Jingmei Mu's work include Wheat and Barley Genetics and Pathology (18 papers), Plant Disease Resistance and Genetics (12 papers) and Genetic Mapping and Diversity in Plants and Animals (11 papers). Jingmei Mu is often cited by papers focused on Wheat and Barley Genetics and Pathology (18 papers), Plant Disease Resistance and Genetics (12 papers) and Genetic Mapping and Diversity in Plants and Animals (11 papers). Jingmei Mu collaborates with scholars based in China, United States and Australia. Jingmei Mu's co-authors include Dejun Han, Zhensheng Kang, Jianhui Wu, Qilin Wang, Qingdong Zeng, Shengjie Liu, Shizhou Yu, Shuo Huang, R. A. McIntosh and Xianming Chen and has published in prestigious journals such as Plant and Soil, Frontiers in Plant Science and Theoretical and Applied Genetics.

In The Last Decade

Jingmei Mu

19 papers receiving 478 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jingmei Mu China 14 470 243 85 50 7 19 481
Luciano da Costa e Silva United States 7 298 0.6× 175 0.7× 37 0.4× 64 1.3× 12 1.7× 11 355
Puyang Ding China 9 369 0.8× 185 0.8× 64 0.8× 75 1.5× 2 0.3× 13 379
Tesfaye Letta Ethiopia 9 388 0.8× 200 0.8× 38 0.4× 79 1.6× 14 2.0× 17 403
Stella Hubbart‐Edwards United Kingdom 13 351 0.7× 89 0.4× 52 0.6× 38 0.8× 18 2.6× 17 366
Sara J. Larsson United States 5 252 0.5× 193 0.8× 57 0.7× 42 0.8× 4 0.6× 7 304
Eric Dinglasan Australia 13 517 1.1× 162 0.7× 58 0.7× 92 1.8× 8 1.1× 32 542
Stephen Ashling United Kingdom 13 418 0.9× 115 0.5× 62 0.7× 41 0.8× 18 2.6× 19 437
Maria Angela Cané Italy 8 555 1.2× 326 1.3× 30 0.4× 118 2.4× 7 1.0× 12 570
Ariel Castro Uruguay 13 482 1.0× 263 1.1× 57 0.7× 62 1.2× 2 0.3× 22 499
Carol Powers United States 9 264 0.6× 116 0.5× 48 0.6× 49 1.0× 3 0.4× 12 278

Countries citing papers authored by Jingmei Mu

Since Specialization
Citations

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

Fields of papers citing papers by Jingmei Mu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jingmei Mu

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

All Works

19 of 19 papers shown
2.
Mu, Jingmei, Lu Liu, Yan Liu, et al.. (2020). Genome-Wide Association Study and Gene Specific Markers Identified 51 Genes or QTL for Resistance to Stripe Rust in U.S. Winter Wheat Cultivars and Breeding Lines. Frontiers in Plant Science. 11. 998–998. 32 indexed citations
3.
Mu, Jingmei, Jianhui Wu, Shengjie Liu, et al.. (2019). Genome-Wide Linkage Mapping Reveals Stripe Rust Resistance in Common Wheat (Triticum aestivum) Xinong1376. Plant Disease. 103(11). 2742–2750. 6 indexed citations
4.
Zeng, Qingdong, Jianhui Wu, Shuo Huang, et al.. (2019). SNP-based linkage mapping for validation of adult plant stripe rust resistance QTL in common wheat cultivar Chakwal 86. The Crop Journal. 7(2). 176–186. 15 indexed citations
5.
Zeng, Qingdong, Jianhui Wu, Shengjie Liu, et al.. (2019). A major QTL co-localized on chromosome 6BL and its epistatic interaction for enhanced wheat stripe rust resistance. Theoretical and Applied Genetics. 132(5). 1409–1424. 17 indexed citations
6.
Mu, Jingmei, Xiaoting Wang, Shuo Huang, et al.. (2019). Combining genome-wide linkage mapping with extreme pool genotyping for stripe rust resistance gene identification in bread wheat. Molecular Breeding. 39(6). 2 indexed citations
7.
Mu, Jingmei, Qilin Wang, Jianhui Wu, et al.. (2019). Identification of sources of resistance in geographically diverse wheat accessions to stripe rust pathogen in China. Crop Protection. 122. 1–8. 12 indexed citations
8.
Huang, Shuo, Jianhui Wu, Xiaoting Wang, et al.. (2019). Utilization of the Genomewide Wheat 55K SNP Array for Genetic Analysis of Stripe Rust Resistance in Common Wheat Line P9936. Phytopathology. 109(5). 819–827. 29 indexed citations
9.
Mu, Jingmei, Shuo Huang, Shengjie Liu, et al.. (2018). Genetic architecture of wheat stripe rust resistance revealed by combining QTL mapping using SNP-based genetic maps and bulked segregant analysis. Theoretical and Applied Genetics. 132(2). 443–455. 30 indexed citations
10.
Wu, Jianhui, Shuo Huang, Qingdong Zeng, et al.. (2018). Comparative genome-wide mapping versus extreme pool-genotyping and development of diagnostic SNP markers linked to QTL for adult plant resistance to stripe rust in common wheat. Theoretical and Applied Genetics. 131(8). 1777–1792. 25 indexed citations
11.
Wu, Jianhui, Qingdong Zeng, Qilin Wang, et al.. (2018). SNP-based pool genotyping and haplotype analysis accelerate fine-mapping of the wheat genomic region containing stripe rust resistance gene Yr26. Theoretical and Applied Genetics. 131(7). 1481–1496. 53 indexed citations
12.
Zeng, Qingdong, Jianhui Wu, Shengjie Liu, et al.. (2018). Genome-wide Mapping for Stripe Rust Resistance Loci in Common Wheat Cultivar Qinnong 142. Plant Disease. 103(3). 439–447. 18 indexed citations
13.
McIntosh, R. A., Jingmei Mu, Dejun Han, & Zhensheng Kang. (2018). Wheat stripe rust resistance gene Yr24/Yr26: A retrospective review. The Crop Journal. 6(4). 321–329. 65 indexed citations
14.
Wu, Jianhui, Shengjie Liu, Qilin Wang, et al.. (2017). Rapid identification of an adult plant stripe rust resistance gene in hexaploid wheat by high-throughput SNP array genotyping of pooled extremes. Theoretical and Applied Genetics. 131(1). 43–58. 57 indexed citations
15.
Li, Haiyang, Qilin Wang, Liangsheng Xu, et al.. (2017). Rapid identification of a major effect QTL conferring adult plant resistance to stripe rust in wheat cultivar Yaco“S”. Euphytica. 213(6). 6 indexed citations
16.
Wu, Jianhui, Qilin Wang, Shengjie Liu, et al.. (2017). Saturation Mapping of a Major Effect QTL for Stripe Rust Resistance on Wheat Chromosome 2B in Cultivar Napo 63 Using SNP Genotyping Arrays. Frontiers in Plant Science. 8. 653–653. 29 indexed citations
18.
Wu, Jianhui, Qilin Wang, Zhensheng Kang, et al.. (2017). Development and Validation of KASP-SNP Markers for QTL Underlying Resistance to Stripe Rust in Common Wheat Cultivar P10057. Plant Disease. 101(12). 2079–2087. 24 indexed citations
19.
Wu, Jianhui, et al.. (2016). Stripe rust resistance in wheat breeding lines developed for central Shaanxi, an overwintering region for Puccinia striiformis f. sp. tritici in China. Canadian Journal of Plant Pathology. 38(3). 317–324. 31 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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