Shaoqing Tang
- Plant Science top 2%
- Molecular Biology
- Genetics top 5%
- Nutrition and Dietetics top 5%
- Pollution top 10%
- Topics
- Food composition and properties (21 papers)GABA and Rice Research (19 papers)Genetic Mapping and Diversity in Plants and Animals (16 papers)
- Partner nations
- ChinaPhilippinesBangladesh
In The Last Decade
Shaoqing Tang
71 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 83
- Plant Science 1.3k
- Molecular Biology 663
- Genetics 395
- Nutrition and Dietetics 277
- Pollution 138
Countries citing papers authored by Shaoqing Tang
This map shows the geographic impact of Shaoqing Tang'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 Shaoqing Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaoqing Tang more than expected).
Fields of papers citing papers by Shaoqing Tang
This network shows the impact of papers produced by Shaoqing Tang. 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 Shaoqing Tang. The network helps show where Shaoqing Tang may publish in the future.
Co-authorship network of co-authors of Shaoqing Tang
This figure shows the co-authorship network connecting the top 25 collaborators of Shaoqing Tang. A scholar is included among the top collaborators of Shaoqing Tang 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 Shaoqing Tang. Shaoqing Tang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 14 | |
| 4 | 4 | |
| 5 | 11 | |
| 6 | 4 | |
| 7 | 165 | |
| 8 | CRISPR/CAS9-mediated editing of the fragrant gene Badh2 in rice. | 33 |
| 9 | 82 | |
| 10 | 38 | |
| 11 | 0 | |
| 12 | 29 | |
| 13 | 62 | |
| 14 | 13 | |
| 15 | 42 | |
| 16 | Starch Pasting Properties and Structure of a High Amylose Rice Mutant Goamy2 | 1 |
| 17 | Disease and insect pest resistance and agronomic traits of rice variety ZH5 with sheath blight resistance | 3 |
| 18 | Analysis of Fat Content in Milled Rice by Near Infrared Reflectance Spectroscopy | 1 |
| 19 | Its Sequences of 8 Aspidistra Species and its Phylogenetic Significance | 2 |
| 20 | Relationship between Camellia nitidissima Chi and C. petelotii (Merr.) Sealy based on nrDNA ITS | 2 |
About Shaoqing Tang
Shaoqing Tang is a scholar working on Plant Science, Nutrition and Dietetics and Analytical Chemistry, having authored 75 papers that have together received 1.8k indexed citations. Recurring topics across this work include Food composition and properties (21 papers), GABA and Rice Research (19 papers) and Genetic Mapping and Diversity in Plants and Animals (16 papers). The work is most often cited by research in Plant Science (1.3k citations), Nutrition and Dietetics (277 citations) and Genetics (395 citations). Shaoqing Tang has collaborated with scholars based in China, Philippines and Bangladesh. Frequent co-authors include Xiangjin Wei, Peisong Hu, Guiai Jiao, Zhonghua Sheng, Gaoneng Shao, Lihong Xie, Zhonghua Sheng, Shikai Hu, Ju Luo and Shakeel Ahmad. Their work appears in journals such as PLoS ONE, Journal of Hazardous Materials and Journal of Agricultural and Food Chemistry.
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.