De‐Wei Wu

1.3k citations
40 papers · 1.1k · h-index 22

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • RNA modifications and cancer
    • Circular RNAs in diseases
    • RNA Research and Splicing

Papers in

    • RNA modifications and cancer 6
    • Wnt/β-catenin signaling in development and cancer 5
    • PI3K/AKT/mTOR signaling in cancer 4
    • RNA Research and Splicing 3
    • MicroRNA in disease regulation 5
    • Cancer-related molecular mechanisms research 4

De‐Wei Wu

40 papers receiving 1.0k citations

Peers

De‐Wei Wu
Comparison fields: 5 of 84
  • Cancer Research 342
  • Molecular Biology 680
  • Oncology 234
  • Immunology 153
  • Cell Biology 87
Replace Shu‐Biao Wu with:
Shu‐Biao Wu China
Qiaofen Fu China
Jinwu Peng China
Jinah Park South Korea
I. B. Zborovskaya Russia
Xiaofang Xing China
Hanxiang Zhan China
Chung-Ta Lee Taiwan
Haihua Qian China
Xiao Qi Wang Hong Kong
De‐Wei Wu relative to Shu‐Biao Wu China Shu‐Biao Wu's profile →
Citations per field
00.5×1.5×
Shu‐Biao Wu · 1×
Citations per year

Countries citing papers authored by De‐Wei Wu

Since Specialization
Citations

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

Fields of papers citing papers by De‐Wei Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010117
2 201188
3 201453
4 202146
5 201446
6 201243
7 201642
8 201741
9 201637
10 201737
11 201636
12 201635
13 201633
14 201733
15 201631
16 201829
17 200528
18 201826
19 202126
20 201525

About De‐Wei Wu

De‐Wei Wu is a scholar working on Molecular Biology, Cancer Research, Immunology, Cardiology and Cardiovascular Medicine and Pulmonary and Respiratory Medicine, having authored 40 papers that have together received 1.1k indexed citations. Recurring topics across this work include RNA modifications and cancer (6 papers), Wnt/β-catenin signaling in development and cancer (5 papers), MicroRNA in disease regulation (5 papers), PI3K/AKT/mTOR signaling in cancer (4 papers), Cancer-related molecular mechanisms research (4 papers), Lung Cancer Treatments and Mutations (4 papers), RNA Research and Splicing (3 papers) and Cancer-related Molecular Pathways (3 papers). The work is most often cited by research in Cancer Research (342 citations), Molecular Biology (680 citations), Oncology (234 citations), Immunology (153 citations) and Cell Biology (87 citations). De‐Wei Wu has collaborated with scholars based in Taiwan, China and Hong Kong. Frequent co-authors include Huei Lee, Ya‐Wen Cheng, Chih‐Yi Chen, Po-Lin Lin, Lee Wang, John Wang, Chi-Chou Huang, Yao-Chen Wang, Huei Lee and Tzu-Chin Wu. Their work appears in journals such as Oncotarget, Scientific Reports, Clinical Cancer Research, Theranostics and Carcinogenesis.

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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