Youping Li

992 citations
37 papers · 652 · h-index 13

Impact in

Papers in

Youping Li

36 papers receiving 638 citations

Peers

Youping Li
Comparison fields: 5 of 108
  • Genetics 131
  • Health, Toxicology and Mutagenesis 148
  • Cancer Research 127
  • Environmental Engineering 82
  • Automotive Engineering 52
Replace Kazuya Inoue with:
Kazuya Inoue Japan
Ming-Dong Zhao China
Yongxun Zhuansun China
Miao Chen China
Christopher Kim United States
Bin Hou China
Yongkui Wang China
Ruijun Xu China
Mark A. D’Andrea United States
Qin Yao China
Youping Li relative to Kazuya Inoue Japan Kazuya Inoue's profile →
Citations per field
00.5×11.9×
Kazuya Inoue · 1×
Citations per year

Countries citing papers authored by Youping Li

Since Specialization
Citations

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

Fields of papers citing papers by Youping Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Youping Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Youping Li Line = papers co-authored together Youping Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008182
2 201576
3 201361
4 201946
5 201732
6 201828
7 201823
8 201721
9 201418
10 201117
11 202217
12 201915
13
miR-137 functions as a tumor suppressor gene in pituitary adenoma by targeting AKT2.
201915
14 201112
15 200610
16 20188
17 20178
18 20236
19 20216
20 20226

About Youping Li

Youping Li is a scholar working on Molecular Biology, Cancer Research, Surgery, Health, Toxicology and Mutagenesis and Genetics, having authored 37 papers that have together received 652 indexed citations. Recurring topics across this work include Circular RNAs in diseases (5 papers), Air Quality and Health Impacts (5 papers), MicroRNA in disease regulation (5 papers), Air Quality Monitoring and Forecasting (4 papers), Cancer-related molecular mechanisms research (4 papers), Xenotransplantation and immune response (3 papers), Glioma Diagnosis and Treatment (3 papers) and Water Quality and Pollution Assessment (2 papers). The work is most often cited by research in Genetics (131 citations), Health, Toxicology and Mutagenesis (148 citations), Cancer Research (127 citations), Environmental Engineering (82 citations) and Automotive Engineering (52 citations). Youping Li has collaborated with scholars based in China, Hong Kong and Canada. Frequent co-authors include Younan Chen, Shengfu Li, Mang Lin, Dalei Wu, Yanrong Lu, Jingqiu Cheng, XU Chun-hua, Dan Long, Lingling Wei and Hong Zhou. Their work appears in journals such as Journal of Evidence-Based Medicine, Blood Cells Molecules and Diseases, Molecular Neurobiology, PLoS ONE and RSC Advances.

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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