Junji Su

1.2k total citations
43 papers, 882 citations indexed

About

Junji Su is a scholar working on Plant Science, Molecular Biology and Endocrinology. According to data from OpenAlex, Junji Su has authored 43 papers receiving a total of 882 indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Plant Science, 12 papers in Molecular Biology and 12 papers in Endocrinology. Recurrent topics in Junji Su's work include Research in Cotton Cultivation (33 papers), Plant and Fungal Interactions Research (12 papers) and Plant Molecular Biology Research (10 papers). Junji Su is often cited by papers focused on Research in Cotton Cultivation (33 papers), Plant and Fungal Interactions Research (12 papers) and Plant Molecular Biology Research (10 papers). Junji Su collaborates with scholars based in China and Brazil. Junji Su's co-authors include Shuxun Yu, Hantao Wang, Hengling Wei, Caixiang Wang, Lijiao Gu, Libei Li, Shuli Fan, Chaoyou Pang, Meizhen Song and Qi Ma and has published in prestigious journals such as PLoS ONE, Scientific Reports and International Journal of Molecular Sciences.

In The Last Decade

Junji Su

41 papers receiving 874 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Junji Su China 17 791 233 128 105 46 43 882
Yinhua Jia China 17 575 0.7× 185 0.8× 88 0.7× 69 0.7× 18 0.4× 54 653
Libei Li China 15 625 0.8× 258 1.1× 113 0.9× 54 0.5× 21 0.5× 34 708
Joy Nyangasi Kirungu China 19 914 1.2× 434 1.9× 47 0.4× 51 0.5× 19 0.4× 31 1.0k
Richard Odongo Magwanga China 23 1.1k 1.4× 527 2.3× 50 0.4× 59 0.6× 22 0.5× 47 1.2k
Muhammad Kashif Riaz Khan Pakistan 12 455 0.6× 102 0.4× 58 0.5× 26 0.2× 32 0.7× 42 492
Pu Lu China 17 800 1.0× 391 1.7× 25 0.2× 43 0.4× 22 0.5× 25 892
Stella K. Kantartzi United States 14 653 0.8× 72 0.3× 78 0.6× 52 0.5× 38 0.8× 62 687
Xinlun Liu China 15 590 0.7× 229 1.0× 81 0.6× 111 1.1× 43 0.9× 43 753
L. Kuntze Germany 7 527 0.7× 152 0.7× 44 0.3× 133 1.3× 31 0.7× 11 583

Countries citing papers authored by Junji Su

Since Specialization
Citations

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

Fields of papers citing papers by Junji Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junji Su

This figure shows the co-authorship network connecting the top 25 collaborators of Junji Su. A scholar is included among the top collaborators of Junji Su 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 Junji Su. Junji Su 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.
Ma, Qi, Xueli Zhang, Jilian Li, et al.. (2025). Identification of Elite Alleles and Candidate Genes for the Cotton Boll Opening Rate via a Genome-Wide Association Study. International Journal of Molecular Sciences. 26(6). 2697–2697. 1 indexed citations
2.
Wei, Wei, et al.. (2024). H3K36 methyltransferase GhKMT3;1a and GhKMT3;2a promote flowering in upland cotton. BMC Plant Biology. 24(1). 739–739. 1 indexed citations
3.
Li, Ying, et al.. (2024). GhASHH1.A and GhASHH2.A Improve Tolerance to High and Low Temperatures and Accelerate the Flowering Response to Temperature in Upland Cotton (Gossypium hirsutum). International Journal of Molecular Sciences. 25(20). 11321–11321. 1 indexed citations
4.
Luo, Jin, Meili Li, Wei Wei, et al.. (2024). Genome-Wide Identification of the GhANN Gene Family and Functional Validation of GhANN11 and GhANN4 under Abiotic Stress. International Journal of Molecular Sciences. 25(3). 1877–1877. 7 indexed citations
5.
Li, Ying, et al.. (2024). GhGASA14 regulates the flowering time of upland cotton in response to GA3. Plant Cell Reports. 43(7). 170–170. 7 indexed citations
6.
Zhang, Xueli, et al.. (2024). The Silencing of GhPIP5K2 and GhPIP5K22 Weakens Abiotic Stress Tolerance in Upland Cotton (Gossypium hirsutum). International Journal of Molecular Sciences. 25(3). 1511–1511. 3 indexed citations
7.
Wei, Wei, Xueli Zhang, Ying Li, et al.. (2024). GhBRX.1, GhBRX.2, and GhBRX4.3 improve resistance to salt and cold stress in upland cotton. Frontiers in Plant Science. 15. 1353365–1353365. 8 indexed citations
8.
9.
Zhang, Feiyan, Linfang Shi, Aimin Chen, et al.. (2023). Cotton RSG2 Mediates Plant Resistance against Verticillium dahliae by miR482b Regulation. Biology. 12(7). 898–898. 2 indexed citations
10.
Wang, Caixiang, Juanjuan Liu, Xiaoyu Xie, et al.. (2022). GhAP1‐D3 positively regulates flowering time and early maturity with no yield and fiber quality penalties in upland cotton. Journal of Integrative Plant Biology. 65(4). 985–1002. 31 indexed citations
11.
Zhou, Tong, Ning Wang, Yuan Wang, et al.. (2022). Nucleotide Evolution, Domestication Selection, and Genetic Relationships of Chloroplast Genomes in the Economically Important Crop Genus Gossypium. Frontiers in Plant Science. 13. 873788–873788. 8 indexed citations
12.
Su, Junji, Caixiang Wang, Qi Ma, et al.. (2020). An RTM-GWAS procedure reveals the QTL alleles and candidate genes for three yield-related traits in upland cotton. BMC Plant Biology. 20(1). 416–416. 26 indexed citations
13.
Li, Mengfei, Yuan Liu, Peipei Zhang, et al.. (2020). Genetic dissection of stem WSC accumulation and remobilization in wheat (Triticum aestivum L.) under terminal drought stress. BMC Genetics. 21(1). 50–50. 14 indexed citations
14.
Zhang, Peipei, Yuan Liu, Mengfei Li, et al.. (2020). Abscisic acid associated with key enzymes and genes involving in dynamic flux of water soluble carbohydrates in wheat peduncle under terminal drought stress. Plant Physiology and Biochemistry. 151. 719–728. 21 indexed citations
15.
Wei, Hengling, Hantao Wang, Junji Su, et al.. (2018). Functional analysis of nine cotton genes related to leaf senescence in Gossypium hirsutum L. Physiology and Molecular Biology of Plants. 24(5). 729–739. 4 indexed citations
16.
Jia, Xiaoyun, Hantao Wang, Chaoyou Pang, et al.. (2018). QTL delineation for five fiber quality traits based on an intra-specific Gossypium hirsutum L. recombinant inbred line population. Molecular Genetics and Genomics. 293(4). 831–843. 11 indexed citations
17.
Sun, Huiru, Pengbo Hao, Qiang Ma, et al.. (2018). Genome-wide identification and expression analyses of the pectate lyase (PEL) gene family in cotton (Gossypium hirsutum L.). BMC Genomics. 19(1). 661–661. 33 indexed citations
18.
Zhao, Shuqi, Chaoyou Pang, Hengling Wei, et al.. (2017). Genetic Inheritance of Earliness Traits in Upland Cotton ( Gossypium hirsutum L.) Inferred by Joint Analysis of Multiple Generations. Mianhua xuebao. 29(2). 119–127. 3 indexed citations
19.
Mao, Guangzhi, Qiang Ma, Hengling Wei, et al.. (2017). Fine mapping and candidate gene analysis of the virescent gene v 1 in Upland cotton (Gossypium hirsutum). Molecular Genetics and Genomics. 293(1). 249–264. 11 indexed citations
20.
Han, Haiming, Li Bai, Junji Su, et al.. (2014). Genetic Rearrangements of Six Wheat–Agropyron cristatum 6P Addition Lines Revealed by Molecular Markers. PLoS ONE. 9(3). e91066–e91066. 54 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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