Yu Wei

555 citations
23 papers · 405 · h-index 13

Impact in

Papers in

Yu Wei

20 papers receiving 394 citations

Peers

Yu Wei
Comparison fields: 5 of 90
  • Computational Theory and Mathematics 119
  • Molecular Medicine 36
  • Hepatology 35
  • Molecular Biology 210
  • Physiology 12
Replace Mónica Rosas‐Lemus with:
Mónica Rosas‐Lemus United States
Himani Tandon India
Lobanov MIu Russia
Galzitskaia Ov Russia
Ana Carolina Ramos Guimarães Brazil
Gulshan Wadhwa India
Abdulrahim R. Hakami Saudi Arabia
Erik L. Allman United States
Jan Blanchard Canada
Thomas Hudson United States
Yu Wei relative to Mónica Rosas‐Lemus United States Mónica Rosas‐Lemus's profile →
Citations per field
00.5×
Mónica Rosas‐Lemus · 1×
Citations per year

Countries citing papers authored by Yu Wei

Since Specialization
Citations

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

Fields of papers citing papers by Yu Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yu Wei, 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 Yu Wei Line = papers co-authored together Yu Wei links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202253
2 201652
3 201647
4 201934
5
Proteomic analysis of synovial fibroblast-like synoviocytes from rheumatoid arthritis.
201332
6 202027
7 202124
8 201522
9 201920
10 201619
11 201917
12 201916
13 202215
14 201810
15 20224
16 20254
17 20204
18 20182
19 20251
20 20161

About Yu Wei

Yu Wei is a scholar working on Molecular Biology, Computational Theory and Mathematics, Mechanics of Materials, Infectious Diseases and Organic Chemistry, having authored 23 papers that have together received 405 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Numerical methods in engineering (3 papers), Receptor Mechanisms and Signaling (3 papers), Bacterial biofilms and quorum sensing (2 papers), Toxin Mechanisms and Immunotoxins (2 papers), Adenosine and Purinergic Signaling (2 papers), Hepatitis C virus research (2 papers) and Geotechnical Engineering and Underground Structures (2 papers). The work is most often cited by research in Computational Theory and Mathematics (119 citations), Molecular Medicine (36 citations), Hepatology (35 citations), Molecular Biology (210 citations) and Physiology (12 citations). Yu Wei has collaborated with scholars based in China, United States and Russia. Frequent co-authors include Jianping Lin, Zhangyong Hong, Zhonglin Li, Yong Jiang, Weiqiang Huang, Wěi Li, Shouguang Jin, Weihui Wu, Yongxin Jin and Jing Shi. Their work appears in journals such as European Journal of Medicinal Chemistry, Bioinformatics, Computational Mechanics, Scientific Reports and Phytochemistry.

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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