Sufang Li

4.3k total citations
135 papers, 2.8k citations indexed

About

Sufang Li is a scholar working on Molecular Biology, Immunology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Sufang Li has authored 135 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Molecular Biology, 25 papers in Immunology and 22 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Sufang Li's work include MicroRNA in disease regulation (16 papers), Immunotherapy and Immune Responses (16 papers) and Circular RNAs in diseases (15 papers). Sufang Li is often cited by papers focused on MicroRNA in disease regulation (16 papers), Immunotherapy and Immune Responses (16 papers) and Circular RNAs in diseases (15 papers). Sufang Li collaborates with scholars based in China, United States and United Kingdom. Sufang Li's 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 and has published in prestigious journals such as SHILAP Revista de lepidopterología, Blood and The Journal of Immunology.

In The Last Decade

Sufang Li

126 papers receiving 2.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sufang Li China 29 874 526 496 483 318 135 2.8k
Yuming Li China 30 724 0.8× 293 0.6× 360 0.7× 259 0.5× 575 1.8× 200 3.4k
Xiaojuan He China 35 1.5k 1.8× 285 0.5× 457 0.9× 337 0.7× 47 0.1× 152 3.9k
Hiroshi Ohta Japan 31 448 0.5× 528 1.0× 135 0.3× 92 0.2× 306 1.0× 249 3.4k
Wu Yao China 31 1.4k 1.6× 120 0.2× 341 0.7× 649 1.3× 160 0.5× 244 3.6k
Fang Xu China 31 627 0.7× 296 0.6× 77 0.2× 135 0.3× 94 0.3× 141 2.9k
Masami Kojima Japan 28 622 0.7× 318 0.6× 124 0.3× 87 0.2× 46 0.1× 203 2.9k
Siying Wang China 29 1.3k 1.5× 133 0.3× 129 0.3× 912 1.9× 78 0.2× 142 3.0k
Wei Pan China 29 813 0.9× 153 0.3× 436 0.9× 279 0.6× 248 0.8× 124 2.8k
Nana Yang China 26 726 0.8× 117 0.2× 172 0.3× 372 0.8× 59 0.2× 109 2.0k
Yingying Li China 26 891 1.0× 262 0.5× 349 0.7× 424 0.9× 103 0.3× 179 2.8k

Countries citing papers authored by Sufang Li

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
2.
Zhang, Feng, Caiyan Zhang, Dan He, et al.. (2025). Noninvasive left ventricular myocardial work identifies subclinical myocardial dysfunction in patients with systemic sclerosis. Clinical Rheumatology. 44(6). 2343–2354.
3.
4.
Zou, Yu, Mo‐Xian Chen, Sufang Li, et al.. (2023). Gut microbiota in children with split-dose bowel preparations revealed by metagenomics. Frontiers in Cellular and Infection Microbiology. 13. 1202007–1202007. 3 indexed citations
5.
Hu, Zhen, Hao Peng, Jingyuan Liu, et al.. (2023). Integrating genetic-engineered cellulose nanofibrils of rice straw with mild chemical treatments for enhanced bioethanol conversion and bioaerogels production. Industrial Crops and Products. 202. 117044–117044. 14 indexed citations
6.
Cui, Yuxia, et al.. (2022). Endothelial Microparticle-Mediated Transfer of microRNA-19b Inhibits the Function and Distribution of Lymphatic Vessels in Atherosclerotic Mice. Frontiers in Physiology. 13. 850298–850298. 2 indexed citations
7.
Chen, Qixin, et al.. (2021). Identification of monocyte-associated genes as predictive biomarkers of heart failure after acute myocardial infarction. BMC Medical Genomics. 14(1). 44–44. 23 indexed citations
8.
Geng, Qiang, et al.. (2019). Efficacy and safety of combined neprilysin and RAS inhibition in heart failure: A meta-analysis of randomized controlled trials. International Journal of Cardiology. 293. 159–164. 10 indexed citations
9.
Li, Changlong, Sufang Li, Feng Zhang, et al.. (2017). Endothelial microparticles-mediated transfer of microRNA-19b promotes atherosclerosis via activating perivascular adipose tissue inflammation in apoE−/− mice. Biochemical and Biophysical Research Communications. 495(2). 1922–1929. 49 indexed citations
10.
11.
Gao, Yuanfeng, Junxian Song, Sufang Li, et al.. (2016). GW27-e0470 Mutations in SCAP and AGXT2 Revealed by Exome Sequencing in a Pedigree with Premature Myocardial Infarction. Journal of the American College of Cardiology. 68(16). C19–C20.
12.
Wang, Liang‐Chen, Liang-Bi Wang, Hongxu Li, et al.. (2015). The effect of ethylene oxide groups in alkyl ethoxy carboxylates on its scale inhibition performance. Desalination. 379. 75–84. 44 indexed citations
13.
Wang, Liang‐Chen, et al.. (2015). Relationships between the characteristics of CaCO 3 fouling and the flow velocity in smooth tube. Experimental Thermal and Fluid Science. 74. 143–159. 38 indexed citations
14.
Li, Jingjin, Jingyi Ren, Junxian Song, et al.. (2015). Effects of statin on circulating microRNAome and predicted function regulatory network in patients with unstable angina. BMC Medical Genomics. 8(1). 12–12. 20 indexed citations
15.
Ren, Wei, et al.. (2014). Association between single nucleotide polymorphisms of PCSK1 and PCSK2 gene and newly diagnosed type 2 diabetes. SHILAP Revista de lepidopterología. 39(12). 961–964. 1 indexed citations
16.
Li, Sufang, Jingyi Ren, Qiang Geng, et al.. (2014). MicroRNA-223 inhibits tissue factor expression in vascular endothelial cells. Atherosclerosis. 237(2). 514–520. 66 indexed citations
17.
Zheng, Xiaoya, Wei Ren, Suhua Zhang, et al.. (2011). 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. SHILAP Revista de lepidopterología. 36(3). 269–272. 2 indexed citations
18.
Zheng, Xiaoya, Wei Ren, Suhua Zhang, et al.. (2010). Serum levels of proamylin and amylin in normal subjects and patients with impaired glucose regulation and type 2 diabetes mellitus. Acta Diabetologica. 47(3). 265–270. 26 indexed citations
19.
Hong, Jian, Ying C. Q. Zang, Sufang Li, Victor M. Rivera, & Jingwu Z. Zhang. (2004). Ex vivo detection of myelin basic protein‐reactive T cells in multiple sclerosis and controls using specific TCR oligonucleotide probes. European Journal of Immunology. 34(3). 870–881. 15 indexed citations
20.
Hong, Jian, Ying C. Q. Zang, Maria V. Tejada‐Simon, et al.. (2000). Reactivity and Regulatory Properties of Human Anti-Idiotypic Antibodies Induced by T Cell Vaccination. The Journal of Immunology. 165(12). 6858–6864. 33 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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