Shunmou Huang

5.7k total citations
28 papers, 1.2k citations indexed

About

Shunmou Huang is a scholar working on Plant Science, Molecular Biology and Genetics. According to data from OpenAlex, Shunmou Huang has authored 28 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Plant Science, 19 papers in Molecular Biology and 6 papers in Genetics. Recurrent topics in Shunmou Huang's work include Genomics and Phylogenetic Studies (7 papers), Chromosomal and Genetic Variations (7 papers) and Plant Disease Resistance and Genetics (6 papers). Shunmou Huang is often cited by papers focused on Genomics and Phylogenetic Studies (7 papers), Chromosomal and Genetic Variations (7 papers) and Plant Disease Resistance and Genetics (6 papers). Shunmou Huang collaborates with scholars based in China, United States and Australia. Shunmou Huang's co-authors include Hanzhong Wang, Wei Hua, Shengyi Liu, Wei Hua, Meiyu Sun, Yumei Liu, Jianbo Song, Tamás Dalmay, Wanxing Wang and Linbin Deng and has published in prestigious journals such as PLoS ONE, Scientific Reports and The Plant Journal.

In The Last Decade

Shunmou Huang

26 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shunmou Huang China 19 840 652 262 92 84 28 1.2k
Sandip M. Kale India 24 1.4k 1.6× 326 0.5× 236 0.9× 18 0.2× 115 1.4× 42 1.5k
Justin N. Vaughn United States 14 644 0.8× 580 0.9× 105 0.4× 24 0.3× 56 0.7× 25 945
Xuanqiang Liang China 21 1.3k 1.5× 487 0.7× 110 0.4× 37 0.4× 325 3.9× 48 1.4k
Sung Han Ok South Korea 20 1.0k 1.2× 872 1.3× 67 0.3× 68 0.7× 14 0.2× 33 1.3k
Vanika Garg India 24 1.7k 2.0× 510 0.8× 344 1.3× 18 0.2× 99 1.2× 55 1.9k
Channapatna S. Prakash United States 16 603 0.7× 376 0.6× 97 0.4× 20 0.2× 126 1.5× 33 735
Jianbin Su China 19 1.8k 2.2× 1.1k 1.7× 82 0.3× 29 0.3× 29 0.3× 30 2.2k
Run Cai China 23 2.5k 3.0× 1.4k 2.2× 807 3.1× 22 0.2× 45 0.5× 65 3.1k
Naeem H. Syed United Kingdom 23 1.8k 2.1× 1.4k 2.1× 311 1.2× 60 0.7× 6 0.1× 37 2.5k
Yumiko Shirano Japan 16 1.8k 2.1× 1.3k 2.0× 64 0.2× 97 1.1× 9 0.1× 19 2.3k

Countries citing papers authored by Shunmou Huang

Since Specialization
Citations

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

Fields of papers citing papers by Shunmou Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shunmou Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Shunmou Huang. A scholar is included among the top collaborators of Shunmou Huang 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 Shunmou Huang. Shunmou Huang 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.
Huang, Shunmou, Yaoxin Wu, Zhiguang Cao, & Xuexi Zhang. (2025). A deep reinforcement learning method for solving Two-Echelon Location-Routing Problem. Computers & Operations Research. 183. 107210–107210.
2.
Yang, Haibo, Zhe Wang, Xiaoqiao Zhai, et al.. (2023). The stability of transcription factor PfSPL1 participates in the response to phytoplasma stress in Paulownia fortunei. International Journal of Biological Macromolecules. 242(Pt 2). 124770–124770.
3.
Huang, Shunmou, Xiaoqiao Zhai, Xiaofan Li, et al.. (2023). N6‐methyladenosine modification changes during the recovery processes for Paulownia witches' broom disease under the methyl methanesulfonate treatment. Plant Direct. 7(7). e508–e508. 3 indexed citations
4.
5.
Huang, Shunmou, et al.. (2017). Selection of reference genes for quantitative real-time RT-PCR on gene expression in Golden Pompano (Trachinotus ovatus). Polish Journal of Veterinary Sciences. 20(3). 583–594. 22 indexed citations
6.
Chen, Yuning, Xiaoping Ren, Xiaojing Zhou, et al.. (2017). Genetic mapping of yield traits using RIL population derived from Fuchuan Dahuasheng and ICG6375 of peanut (Arachis hypogaea L.). Molecular Breeding. 37(2). 17–17. 35 indexed citations
7.
Zhou, Xiaojing, Yang Dong, Li Huang, et al.. (2016). Genomic survey sequencing for development and validation of single-locus SSR markers in peanut (Arachis hypogaea L.). BMC Genomics. 17(1). 420–420. 30 indexed citations
8.
Li, Yunjing, Jun Li, Yuhua Wu, et al.. (2016). Successful detection of foreign inserts in transgenic rice TT51‐1 (BT63) by RNA‐sequencing combined with PCR. Journal of the Science of Food and Agriculture. 97(5). 1634–1639. 1 indexed citations
9.
Shi, Jiaqin, Jiepeng Zhan, Yuhua Yang, et al.. (2015). Linkage and regional association analysis reveal two new tightly-linked major-QTLs for pod number and seed number per pod in rapeseed (Brassica napus L.). Scientific Reports. 5(1). 14481–14481. 57 indexed citations
10.
Chen, Yuning, Xiaoping Ren, Xiaojing Zhou, et al.. (2014). Dynamics in the resistant and susceptible peanut (Arachis hypogaea L.) root transcriptome on infection with the Ralstonia solanacearum. BMC Genomics. 15(1). 1078–1078. 46 indexed citations
11.
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13.
Huang, Shunmou, Linbin Deng, Mei Guan, et al.. (2013). Identification of genome-wide single nucleotide polymorphisms in allopolyploid crop Brassica napus. BMC Genomics. 14(1). 717–717. 44 indexed citations
14.
Yu, Jingyin, Meixia Zhao, Xiaowu Wang, et al.. (2013). Bolbase: a comprehensive genomics database for Brassica oleracea. BMC Genomics. 14(1). 664–664. 84 indexed citations
15.
Shi, Jiaqin, Shunmou Huang, Donghui Fu, et al.. (2013). Evolutionary Dynamics of Microsatellite Distribution in Plants: Insight from the Comparison of Sequenced Brassica, Arabidopsis and Other Angiosperm Species. PLoS ONE. 8(3). e59988–e59988. 36 indexed citations
16.
Sun, Meiyu, Wei Hua, Shunmou Huang, et al.. (2012). Design of New Genome- and Gene-Sourced Primers and Identification of QTL for Seed Oil Content in a Specially High-Oil Brassica napus Cultivar. PLoS ONE. 7(10). e47037–e47037. 44 indexed citations
17.
Liu, Jing, Shunmou Huang, Meiyu Sun, et al.. (2012). An improved allele-specific PCR primer design method for SNP marker analysis and its application. Plant Methods. 8(1). 34–34. 185 indexed citations
18.
Hu, Zhiyong, Wei Hua, Shunmou Huang, et al.. (2012). Discovery of Pod Shatter-Resistant Associated SNPs by Deep Sequencing of a Representative Library Followed by Bulk Segregant Analysis in Rapeseed. PLoS ONE. 7(4). e34253–e34253. 25 indexed citations
19.
Dong, Caihua, Chen Li, Xiaohong Yan, et al.. (2011). Gene expression profiling of Sinapis alba leaves under drought stress and rewatering growth conditions with Illumina deep sequencing. Molecular Biology Reports. 39(5). 5851–5857. 15 indexed citations
20.
Hu, Zhiyong, Wei Hua, Shunmou Huang, & Hanzhong Wang. (2010). Complete chloroplast genome sequence of rapeseed (Brassica napus L.) and its evolutionary implications. Genetic Resources and Crop Evolution. 58(6). 875–887. 37 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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