Ding Wu

982 citations
29 papers · 771 · h-index 15

Impact in

Papers in

    • Advanced Biosensing Techniques and Applications 5
    • Cancer Cells and Metastasis 2
    • HER2/EGFR in Cancer Research 2

Ding Wu

26 papers receiving 765 citations

Peers

Ding Wu
Comparison fields: 5 of 98
  • Cancer Research 125
  • Aging 15
  • Molecular Biology 390
  • Pathology and Forensic Medicine 89
  • Immunology and Allergy 28
Replace Qun Niu with:
Qun Niu China
Michelle Wong United States
Chu‐yan Chan Hong Kong
Franca Maria Tuccillo Italy
Kuan-Lin Kuo Taiwan
Y-X Zeng China
Kate E. Jarman Australia
Shen‐Wu Wang China
Saw Kyin United States
Nora D. Mineva United States
Ding Wu relative to Qun Niu China Qun Niu's profile →
Citations per field
00.5×2×3×3.8×
Qun Niu · 1×
Citations per year

Countries citing papers authored by Ding Wu

Since Specialization
Citations

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

Fields of papers citing papers by Ding Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019116
2 2017112
3 200285
4 202172
5 201545
6 201644
7 201540
8 201034
9 200532
10 202030
11 200720
12 201517
13 200617
14 202215
15 201014
16 202011
17 202011
18 200510
19 20179
20 20199

About Ding Wu

Ding Wu is a scholar working on Molecular Biology, Oncology, Radiology, Nuclear Medicine and Imaging, Cancer Research and Pulmonary and Respiratory Medicine, having authored 29 papers that have together received 771 indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (7 papers), Advanced Biosensing Techniques and Applications (5 papers), Chronic Myeloid Leukemia Treatments (4 papers), Cancer-related molecular mechanisms research (4 papers), Telomeres, Telomerase, and Senescence (3 papers), Renal cell carcinoma treatment (2 papers), Cancer Cells and Metastasis (2 papers) and HER2/EGFR in Cancer Research (2 papers). The work is most often cited by research in Cancer Research (125 citations), Aging (15 citations), Molecular Biology (390 citations), Pathology and Forensic Medicine (89 citations) and Immunology and Allergy (28 citations). Ding Wu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Stephen J. Kron, Don Wolfgeher, Amy C. Flor, Xiaoqing Sun, Zhan Shi, Laurie L. Parker, Song Xue, Phillip J. DeChristopher, K. Christopher García and Andrew J. Maniotis. Their work appears in journals such as Journal of Biosciences, Analytical Biochemistry, Tumor Biology, Cell Death Discovery and Cellular and Molecular Biology.

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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