Ke Wu

2.0k citations
86 papers · 1.5k indexed · h-index 21

Impact in

Papers in

    • Cancer, Hypoxia, and Metabolism 6
    • Metabolism, Diabetes, and Cancer 11
    • RNA modifications and cancer 8
    • Genomics, phytochemicals, and oxidative stress 4
    • PI3K/AKT/mTOR signaling in cancer 4

Ke Wu

79 papers receiving 1.4k citations

Peers

Ke Wu
Comparison fields: 5 of 108
  • Cancer Research 227
  • Complementary and alternative medicine 100
  • Molecular Biology 800
  • Endocrinology, Diabetes and Metabolism 146
  • Biochemistry 43
Replace Ying Sun with:
Ying Sun China
Arumugam Nagalingam United States
Bruna Pucci Italy
Xue Zhu China
Xin Hua Liu China
Sabu Abraham India
Chi‐Wai Wong China
Swayam Prakash Srivastava United States
Fang Fang China
Ke Wu relative to Ying Sun China Ying Sun's profile →
Citations per field
00.5×1.5×1.8×
Ying Sun · 1×
Citations per year

Countries citing papers authored by Ke Wu

Since Specialization
Citations

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

Fields of papers citing papers by Ke Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20258
2 20252
3 20251
4 20250
5 20243
6 20241
7 20248
8 20241
9 20245
10 20232
11 20230
12 20213
13 20217
14 201915
15 201812
16 201742
17 201339
18 201353
19 20121
20 200548

About Ke Wu

Ke Wu is a scholar working on Cancer Research, Molecular Biology, Hepatology, Oncology and Developmental Biology, having authored 86 papers that have together received 1.5k indexed citations. Recurring topics across this work include Metabolism, Diabetes, and Cancer (11 papers), RNA modifications and cancer (8 papers), Cancer, Hypoxia, and Metabolism (6 papers), Pancreatic and Hepatic Oncology Research (5 papers), Adipose Tissue and Metabolism (5 papers), Hepatocellular Carcinoma Treatment and Prognosis (5 papers), Genomics, phytochemicals, and oxidative stress (4 papers) and PI3K/AKT/mTOR signaling in cancer (4 papers). The work is most often cited by research in Cancer Research (227 citations), Complementary and alternative medicine (100 citations), Molecular Biology (800 citations), Endocrinology, Diabetes and Metabolism (146 citations) and Biochemistry (43 citations). Ke Wu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Yong Wu, Jingping Ouyang, Xianqing Mao, Min Liu, Jaydutt V. Vadgama, Feng Zou, Yunfeng Zhou, Ya Wang, Guobin Wang and Kaixiong Tao. Their work appears in journals such as Antioxidants and Redox Signaling, Acta Pharmacologica Sinica, Cancer Cell International, Journal of Ethnopharmacology and Oncotarget.

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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