Yu Wei

22 papers receiving 426 citations

Peers

Yu Wei
Comparison fields: 5 of 89
  • Molecular Medicine 37
  • Computational Theory and Mathematics 121
  • Hepatology 33
  • Molecular Biology 207
  • Physiology 12
Replace Mónica Rosas‐Lemus with:
Mónica Rosas‐Lemus United States
Himani Tandon India
Galzitskaia Ov Russia
Jan Blanchard Canada
Víctor Sebastián-Pérez Spain
Ana Carolina Ramos Guimarães Brazil
Bader S. Alotaibi Saudi Arabia
Erik L. Allman United States
Abdulrahim R. Hakami Saudi Arabia
Chunmei Jin China
Yu Wei relative to Mónica Rosas‐Lemus United States Mónica Rosas‐Lemus's profile →
Citations per field
00.5×3.8×
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 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202260
2 201653
3 201649
4 201935
5
Proteomic analysis of synovial fibroblast-like synoviocytes from rheumatoid arthritis.
201332
6 202030
7 202124
8 201523
9 201621
10 201921
11 202219
12 201917
13 201916
14 201812
15 20258
16 20224
17 20204
18 20182
19 20252
20 20251

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 25 papers that have together received 435 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), Adenosine and Purinergic Signaling (2 papers), HIV/AIDS drug development and treatment (2 papers), Hepatitis C virus research (2 papers), Antibiotic Resistance in Bacteria (2 papers) and Traditional Chinese Medicine Analysis (2 papers). The work is most often cited by research in Molecular Medicine (37 citations), Computational Theory and Mathematics (121 citations), Hepatology (33 citations), Molecular Biology (207 citations) and Physiology (12 citations). Yu Wei has collaborated with scholars based in China, United States and Hungary. Frequent co-authors include Jianping Lin, Zhangyong Hong, Zhonglin Li, Weiqiang Huang, Yong Jiang, Wěi Li, Zhihui Cheng, Shouguang Jin, Weihui Wu and Xiaolei Pan. Their work appears in journals such as Bioinformatics, European Journal of Medicinal Chemistry, Oxidative Medicine and Cellular Longevity, Computational Mechanics and Engineering Failure Analysis.

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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