Yan‐Ling Wu

4.5k total citations · 1 hit paper
154 papers, 3.6k citations indexed

About

Yan‐Ling Wu is a scholar working on Molecular Biology, Epidemiology and Hepatology. According to data from OpenAlex, Yan‐Ling Wu has authored 154 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Molecular Biology, 53 papers in Epidemiology and 37 papers in Hepatology. Recurrent topics in Yan‐Ling Wu's work include Liver Disease Diagnosis and Treatment (43 papers), Liver physiology and pathology (32 papers) and Drug-Induced Hepatotoxicity and Protection (18 papers). Yan‐Ling Wu is often cited by papers focused on Liver Disease Diagnosis and Treatment (43 papers), Liver physiology and pathology (32 papers) and Drug-Induced Hepatotoxicity and Protection (18 papers). Yan‐Ling Wu collaborates with scholars based in China, Sweden and United States. Yan‐Ling Wu's co-authors include Ji‐Xing Nan, Li‐Hua Lian, Ting Bai, Ying Wan, Quan Jin, Youli Yao, Ben‐Wen Cui, Xin Han, Yong Yang and Peng Sun and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Diabetes.

In The Last Decade

Yan‐Ling Wu

149 papers receiving 3.5k citations

Hit Papers

Photo-driven cycling electro-Fenton catalysis via the syn... 2025 2026 2025 5 10 15 20 25

Peers

Yan‐Ling Wu
Comparison fields: 5 of 136
  • Molecular Biology 1.4k
  • Epidemiology 831
  • Pharmacology 621
  • Hepatology 454
  • Pathology and Forensic Medicine 350
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Xu Han China
Huijun Sun China
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Jingyuan Wan China
Ying Wan China
Cen Xie China
José E. Manautou United States
Dong Hwan Sohn South Korea
Youwei Xu China View profile →
Citations per field, relative to Yan‐Ling Wu
Yan‐Ling Wu · 1×
Citations per year, relative to Yan‐Ling Wu
Yan‐Ling Wu · 1×

Countries citing papers authored by Yan‐Ling Wu

Since Specialization
Citations

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

Fields of papers citing papers by Yan‐Ling Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yan‐Ling Wu. 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 Yan‐Ling Wu. The network helps show where Yan‐Ling Wu may publish in the future.

Co-authorship network of co-authors of Yan‐Ling Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Yan‐Ling Wu. A scholar is included among the top collaborators of Yan‐Ling Wu 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 Yan‐Ling Wu. Yan‐Ling Wu 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
# Work Indexed citations
1 2
2 0
3 0
4 9
5 4
6 8
7 54
8 60
9 5
10 5
11 6
12 1
13 56
14 3
15 6
16 12
17 11
18 102
19 47
20
[Regulatory T cell based transplant tolerance--freedom from immunosuppression].
5

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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