Dinglan Wu

1.7k citations
47 papers · 1.2k · h-index 23

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • Cancer, Lipids, and Metabolism
  • Oncology top 10%
    • CAR-T cell therapy research

Papers in

Dinglan Wu

41 papers receiving 1.2k citations

Peers

Dinglan Wu
Comparison fields: 5 of 99
  • Cancer Research 319
  • Oncology 235
  • Molecular Biology 557
  • Pulmonary and Respiratory Medicine 200
  • Genetics 165
Replace Weiwei Li with:
Weiwei Li China
Toshiyuki Tsunoda Japan
Junchen Liu China
Esra Erdal Türkiye
Julio C. Tapia Chile
Farzaneh Pirnia United States
Zhe Jiang China
Laura Braccini Italy
Anna Rita Cantelmo Italy
Dinglan Wu relative to Weiwei Li China Weiwei Li's profile →
Citations per field
00.5×1.7×
Weiwei Li · 1×
Citations per year

Countries citing papers authored by Dinglan Wu

Since Specialization
Citations

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

Fields of papers citing papers by Dinglan Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2022112
2 202390
3 200889
4 201477
5 201459
6 201854
7 201847
8 201644
9 201842
10 201842
11 201540
12 201939
13 201838
14 202337
15 201935
16 201235
17 201933
18 201727
19 201826
20 202124

About Dinglan Wu

Dinglan Wu is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Cancer Research, Cellular and Molecular Neuroscience and Oncology, having authored 47 papers that have together received 1.2k indexed citations. Recurring topics across this work include Prostate Cancer Treatment and Research (7 papers), Estrogen and related hormone effects (6 papers), Circular RNAs in diseases (6 papers), Nuclear Receptors and Signaling (4 papers), Epigenetics and DNA Methylation (4 papers), Cancer-related molecular mechanisms research (3 papers), Nitric Oxide and Endothelin Effects (2 papers) and Cancer Cells and Metastasis (2 papers). The work is most often cited by research in Cancer Research (319 citations), Oncology (235 citations), Molecular Biology (557 citations), Pulmonary and Respiratory Medicine (200 citations) and Genetics (165 citations). Dinglan Wu has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Franky Leung Chan, Shan Yu, Yuliang Wang, Chi‐Fai Ng, Zhu Wang, Chang Zou, Zhenyu Xu, Xiaoqiang Yao, Jiayi Zhou and Zhenyu Xu. Their work appears in journals such as Oncogene, Stem Cell Research & Therapy, The Journal of Pathology, Journal for ImmunoTherapy of Cancer and Cancer Letters.

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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