Dang Wu

3.8k total citations · 1 hit paper
56 papers, 2.5k citations indexed

About

Dang Wu is a scholar working on Oncology, Immunology and Molecular Biology. According to data from OpenAlex, Dang Wu has authored 56 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Oncology, 22 papers in Immunology and 20 papers in Molecular Biology. Recurrent topics in Dang Wu's work include Cancer Immunotherapy and Biomarkers (11 papers), Immune Cell Function and Interaction (11 papers) and Immune cells in cancer (7 papers). Dang Wu is often cited by papers focused on Cancer Immunotherapy and Biomarkers (11 papers), Immune Cell Function and Interaction (11 papers) and Immune cells in cancer (7 papers). Dang Wu collaborates with scholars based in China, United States and Taiwan. Dang Wu's co-authors include Pin Wu, Jian Huang, Ying Chai, Jun Ye, Zhigang Chen, Li‐Jun Li, Fuming Qiu, Zhigang Zhang, Chao Ni and Lufeng Zhao and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Dang Wu

51 papers receiving 2.5k citations

Hit Papers

Radiation-induced tumor immune microenvironments and pote... 2023 2026 2024 2025 2023 25 50 75 100

Peers

Dang Wu
Comparison fields: 5 of 106
  • Oncology 1.1k
  • Molecular Biology 934
  • Immunology 802
  • Cancer Research 564
  • Pulmonary and Respiratory Medicine 333
Replace Michael J. Campbell with:
Michael J. Campbell United States
Pedro Miguel Lacal Italy
Yanhong Gu China
An Wouters Belgium
Sizhi Paul Gao United States
Manabu Emi Japan
Rachel A. O’Keefe United States
Guocan Wang United States
Michael J. Campbell United States View profile →
Citations per field, relative to Dang Wu
Dang Wu · 1×
Citations per year, relative to Dang Wu
Dang Wu · 1×

Countries citing papers authored by Dang Wu

Since Specialization
Citations

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

Fields of papers citing papers by Dang Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dang Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Dang Wu. A scholar is included among the top collaborators of Dang 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 Dang Wu. Dang 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 0
2 0
3 0
4 4
5 0
6
Radiation-induced tumor immune microenvironments and potential targets for combination therapy breakdown →
109
7 10
8 8
9 14
10 8
11 95
12 81
13 12
14 81
15 71
16 177
17 98
18 142
19 58
20 51

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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