Yun Wu

86 total papers · 669 total citations
43 papers, 487 citations indexed

About

Yun Wu is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Psychiatry and Mental health. According to data from OpenAlex, Yun Wu has authored 43 papers receiving a total of 487 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 6 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Psychiatry and Mental health. Recurrent topics in Yun Wu's work include Carcinogens and Genotoxicity Assessment (4 papers), Toxic Organic Pollutants Impact (3 papers) and Acupuncture Treatment Research Studies (3 papers). Yun Wu is often cited by papers focused on Carcinogens and Genotoxicity Assessment (4 papers), Toxic Organic Pollutants Impact (3 papers) and Acupuncture Treatment Research Studies (3 papers). Yun Wu collaborates with scholars based in China, United States and Israel. Yun Wu's co-authors include Eric H. Weyand, Longjiang Yu, Daoxian Yuan, Shruti Patel, Yung-Cheng Chen, Harold A. Dunsford, Wei Li, Qiufang He, Lewis V. Rodriguez and Aruna Koganti and has published in prestigious journals such as Journal of Clinical Oncology, Analytical Chemistry and The Science of The Total Environment.

In The Last Decade

Yun Wu

40 papers receiving 466 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Yun Wu 111 110 99 52 44 43 487
Mohammad Ali Arif 42 0.4× 159 1.4× 108 1.1× 24 0.5× 43 1.0× 40 520
Jing Rong 49 0.4× 137 1.2× 26 0.3× 25 0.5× 36 0.8× 32 415
Lin Jing 21 0.2× 143 1.3× 30 0.3× 37 0.7× 33 0.8× 41 483
Hui Hua 33 0.3× 152 1.4× 74 0.7× 26 0.5× 25 0.6× 35 448
Chunyan Zhu 73 0.7× 245 2.2× 19 0.2× 14 0.3× 65 1.5× 29 535
A J Sasco 63 0.6× 83 0.8× 90 0.9× 24 0.5× 103 2.3× 16 519
Xuefeng Ren 47 0.4× 188 1.7× 186 1.9× 13 0.3× 21 0.5× 29 522
Jieyu Liu 33 0.3× 84 0.8× 41 0.4× 23 0.4× 29 0.7× 70 506
Mari Tanigawa 16 0.1× 114 1.0× 44 0.4× 46 0.9× 30 0.7× 26 471
Weiwei Duan 51 0.5× 77 0.7× 159 1.6× 20 0.4× 20 0.5× 34 504

Countries citing papers authored by Yun Wu

Since Specialization
Citations

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

Fields of papers citing papers by Yun Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yun Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Yun Wu. A scholar is included among the top collaborators of Yun 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 Yun Wu. Yun Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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