Bingran Zhao

2.0k total citations
43 papers, 1.2k citations indexed

About

Bingran Zhao is a scholar working on Plant Science, Molecular Biology and Genetics. According to data from OpenAlex, Bingran Zhao has authored 43 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Plant Science, 21 papers in Molecular Biology and 11 papers in Genetics. Recurrent topics in Bingran Zhao's work include GABA and Rice Research (11 papers), Genetic Mapping and Diversity in Plants and Animals (10 papers) and Rice Cultivation and Yield Improvement (10 papers). Bingran Zhao is often cited by papers focused on GABA and Rice Research (11 papers), Genetic Mapping and Diversity in Plants and Animals (10 papers) and Rice Cultivation and Yield Improvement (10 papers). Bingran Zhao collaborates with scholars based in China, United States and Hong Kong. Bingran Zhao's co-authors include Bigang Mao, Chengcai Chu, Shuyu Li, Chuanyou Li, Jiaqiang Sun, Qian Qian, Li Tang, Longping Yuan, Dingyang Yuan and Citao Liu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Bingran Zhao

41 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
Bingran Zhao China 14 1.0k 527 429 88 39 43 1.2k
Davoud Torkamaneh Canada 21 1.0k 1.0× 418 0.8× 332 0.8× 42 0.5× 35 0.9× 77 1.3k
Jinkun Du China 15 1.1k 1.1× 444 0.8× 206 0.5× 46 0.5× 27 0.7× 35 1.2k
Huayu Zhu China 17 1.2k 1.1× 573 1.1× 481 1.1× 29 0.3× 55 1.4× 48 1.5k
Tomotaro Nishikawa Japan 15 597 0.6× 798 1.5× 202 0.5× 81 0.9× 92 2.4× 32 1.2k
Shunmou Huang China 19 840 0.8× 652 1.2× 262 0.6× 17 0.2× 22 0.6× 28 1.2k
Caroline Pont France 22 1.5k 1.4× 626 1.2× 480 1.1× 63 0.7× 24 0.6× 29 1.6k
Xueli An China 25 1.6k 1.6× 1.2k 2.3× 164 0.4× 77 0.9× 32 0.8× 49 1.9k
Xingming Hu China 14 1.2k 1.2× 556 1.1× 466 1.1× 37 0.4× 9 0.2× 25 1.4k
Youlin Zhu China 12 792 0.8× 346 0.7× 161 0.4× 15 0.2× 24 0.6× 30 975
Hai Zhou China 22 1.1k 1.0× 826 1.6× 174 0.4× 16 0.2× 14 0.4× 44 1.4k

Countries citing papers authored by Bingran Zhao

Since Specialization
Citations

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

Fields of papers citing papers by Bingran Zhao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bingran Zhao

This figure shows the co-authorship network connecting the top 25 collaborators of Bingran Zhao. A scholar is included among the top collaborators of Bingran Zhao 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 Bingran Zhao. Bingran Zhao 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.
Zhang, Dan, Yuanyi Hu, Li Tang, et al.. (2024). Research on Physiological Characteristics and Differential Gene Expression of Rice Hybrids and Their Parents under Salt Stress at Seedling Stage. Plants. 13(5). 744–744. 1 indexed citations
2.
Zhang, Xiuli, Qing Wang, Li Tang, et al.. (2023). Utilizing differences in bTH tolerance between the parents of two-line hybrid rice to improve the purity of hybrid rice seed. Frontiers in Plant Science. 14. 1217893–1217893. 1 indexed citations
3.
Zheng, Wenjie, Peng Yan, Ye Shao, et al.. (2023). OsPMS1 Mutation Enhances Salt Tolerance by Suppressing ROS Accumulation, Maintaining Na+/K+ Homeostasis, and Promoting ABA Biosynthesis. Genes. 14(8). 1621–1621. 5 indexed citations
4.
Zhang, Yaqun, et al.. (2022). LncRNA-mRNA integrated profiling analysis in response to white spot syndrome virus in hepatopancreas in Penaeus japonicus. Fish & Shellfish Immunology. 129. 251–262. 9 indexed citations
5.
Peng, Yan, Bigang Mao, Changquan Zhang, et al.. (2021). Influence of physicochemical properties and starch fine structure on the eating quality of hybrid rice with similar apparent amylose content. Food Chemistry. 353. 129461–129461. 78 indexed citations
6.
7.
Peng, Yan, Bigang Mao, Changquan Zhang, et al.. (2021). Correlations Between Parental Lines and Indica Hybrid Rice in Terms of Eating Quality Traits. Frontiers in Nutrition. 7. 583997–583997. 7 indexed citations
8.
Shao, Ye, Yan Peng, Bigang Mao, et al.. (2020). Allelic variations of the Wx locus in cultivated rice and their use in the development of hybrid rice in China. PLoS ONE. 15(5). e0232279–e0232279. 15 indexed citations
9.
Hu, Yuanyi, Bigang Mao, Yumei Xia, et al.. (2020). Spike-Stalk Injection Method Causes Extensive Phenotypic and Genotypic Variations for Rice Germplasm. Frontiers in Plant Science. 11. 575373–575373. 2 indexed citations
10.
11.
Liu, Citao, Shujun Ou, Bigang Mao, et al.. (2018). Early selection of bZIP73 facilitated adaptation of japonica rice to cold climates. Nature Communications. 9(1). 3302–3302. 190 indexed citations
12.
Yang, Liyu, et al.. (2016). Genome-wide transcriptome analysis of female-sterile rice ovule shed light on its abortive mechanism. Planta. 244(5). 1011–1028. 17 indexed citations
13.
Zhou, Hai, Ming He, Jing Li, et al.. (2016). Development of Commercial Thermo-sensitive Genic Male Sterile Rice Accelerates Hybrid Rice Breeding Using the CRISPR/Cas9-mediated TMS5 Editing System. Scientific Reports. 6(1). 37395–37395. 168 indexed citations
14.
Peng, Yan, Yuanyi Hu, Bigang Mao, et al.. (2015). Genetic analysis for rice grain quality traits in the YVB stable variant line using RAD-seq. Molecular Genetics and Genomics. 291(1). 297–307. 32 indexed citations
15.
Yuan, Zuoqing, Jianyong Zhang, & Bingran Zhao. (2014). Molecular cloning and expression pattern of the DjStag gene in the planarian Dugesia japonica during embryonic development. Genetics and Molecular Research. 13(1). 188–197. 1 indexed citations
16.
Hu, Yuanyi, Bigang Mao, Yan Peng, et al.. (2014). Deep re-sequencing of a widely used maintainer line of hybrid rice for discovery of DNA polymorphisms and evaluation of genetic diversity. Molecular Genetics and Genomics. 289(3). 303–315. 17 indexed citations
17.
Zhao, Bingran. (2013). Phenotypic Difference and Gene Variation in Agronomic Traits between a Rice Variant with Introduced Exogenous Genomic DNA and Its Receptor. Zajiao shuidao. 4 indexed citations
18.
Zhao, Bingran. (2006). Association Between Estrogen Receptor Alpha Gene Variation And Risks Of Cardiovascular Disease. 2 indexed citations
19.
Zhao, Bingran, et al.. (2004). SSR analysis of the variants from rice maintainer lines transferred exogenous DNA. Zajiao shuidao. 19(4). 47–50. 1 indexed citations
20.
Zhao, Bingran, et al.. (1998). A study on the transportation way of exogenous DNA in vivo and a female sterile variant of rice. JOURNAL OF HUNAN AGRICULTURAL UNIVERSITY. 24(6). 436–441. 7 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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