Sufang Li
- Molecular Biology top 10%
- Economics and Econometrics top 2%
- Immunology top 5%
- Cancer Research top 5%
- Cardiology and Cardiovascular Medicine top 5%
- Co-authors
- Junxian SongHuiming ZhuDi YuanRong LiChongyou LeeHong ChenJingyi RenYing C. Q. Zang
- Topics
- MicroRNA in disease regulation (16 papers)Immunotherapy and Immune Responses (16 papers)Circular RNAs in diseases (15 papers)
- Journals
- SHILAP Revista de lepidopterologíaBloodThe Journal of Immunology
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Sufang Li
126 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 163
- Molecular Biology 874
- Economics and Econometrics 526
- Immunology 496
- Cancer Research 483
- Cardiology and Cardiovascular Medicine 318
Countries citing papers authored by Sufang Li
This map shows the geographic impact of Sufang Li'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 Sufang Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sufang Li more than expected).
Fields of papers citing papers by Sufang Li
This network shows the impact of papers produced by Sufang Li. 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 Sufang Li. The network helps show where Sufang Li may publish in the future.
Co-authorship network of co-authors of Sufang Li
This figure shows the co-authorship network connecting the top 25 collaborators of Sufang Li. A scholar is included among the top collaborators of Sufang Li 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 Sufang Li. Sufang Li 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 | 0 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 14 | |
| 6 | 2 | |
| 7 | 23 | |
| 8 | 10 | |
| 9 | 49 | |
| 10 | 2 | |
| 11 | 0 | |
| 12 | 44 | |
| 13 | 38 | |
| 14 | 20 | |
| 15 | Association between single nucleotide polymorphisms of PCSK1 and PCSK2 gene and newly diagnosed type 2 diabetes | 1 |
| 16 | 66 | |
| 17 | Correlation between single nucleotide polymorphisms of rs7903146 and rs11196218 at TCF7L2 gene and the early phase insulin secretion of newly diagnosed patients with type 2 diabetes | 2 |
| 18 | 26 | |
| 19 | 15 | |
| 20 | 33 |
About Sufang Li
Sufang Li is a scholar working on Cancer Research, Immunology and General Energy, having authored 135 papers that have together received 2.8k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (16 papers), Immunotherapy and Immune Responses (16 papers) and Circular RNAs in diseases (15 papers). The work is most often cited by research in General Energy (65 citations), Cancer Research (483 citations) and Immunology (496 citations). Sufang Li has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Junxian Song, Huiming Zhu, Di Yuan, Rong Li, Chongyou Lee, Hong Chen, Jingyi Ren, Ying C. Q. Zang, Jingwu Z. Zhang and Jian Hong. Their work appears in journals such as SHILAP Revista de lepidopterología, Blood and The Journal of Immunology.
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.