Dabing Huang

664 citations
30 papers · 534 · h-index 15

Impact in

Papers in

    • RNA modifications and cancer 6
    • Cancer-related gene regulation 4
    • Epigenetics and DNA Methylation 3
    • TGF-β signaling in diseases 2
    • Cancer-related molecular mechanisms research 5
    • Cancer, Hypoxia, and Metabolism 3

Dabing Huang

28 papers receiving 517 citations

Peers

Dabing Huang
Comparison fields: 5 of 84
  • Cancer Research 142
  • Endocrine and Autonomic Systems 55
  • Aging 10
  • Reproductive Medicine 45
  • Molecular Biology 276
Replace Chao‐Tien Hsu with:
Chao‐Tien Hsu Taiwan
Qinghui Xiong China
Min Jeong Choi South Korea
Hui Wu China
Sarah Anissa Hannou France
Shuyu Gui China
Vera Lemos Switzerland
Petra Tollet‐Egnell Sweden
Fengsheng Yu China
Chan Wu China
Dabing Huang relative to Chao‐Tien Hsu Taiwan Chao‐Tien Hsu's profile →
Citations per field
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Chao‐Tien Hsu · 1×
Citations per year

Countries citing papers authored by Dabing Huang

Since Specialization
Citations

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

Fields of papers citing papers by Dabing Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200991
2 201054
3 201240
4 201739
5 201033
6 201728
7 201526
8 202125
9 201924
10 202124
11 202321
12 201020
13 201316
14 201814
15 202314
16 201914
17 202010
18 20239
19 20209
20 20227

About Dabing Huang

Dabing Huang is a scholar working on Molecular Biology, Cancer Research, Surgery, Oncology and Epidemiology, having authored 30 papers that have together received 534 indexed citations. Recurring topics across this work include RNA modifications and cancer (6 papers), Cancer-related molecular mechanisms research (5 papers), Cancer-related gene regulation (4 papers), Epigenetics and DNA Methylation (3 papers), 3D Printing in Biomedical Research (3 papers), Cancer, Hypoxia, and Metabolism (3 papers), TGF-β signaling in diseases (2 papers) and Liver Disease Diagnosis and Treatment (2 papers). The work is most often cited by research in Cancer Research (142 citations), Endocrine and Autonomic Systems (55 citations), Aging (10 citations), Reproductive Medicine (45 citations) and Molecular Biology (276 citations). Dabing Huang has collaborated with scholars based in China and Japan. Frequent co-authors include Shilian Hu, Gan Shen, Shi Yin, Xiaodong Jiang, Zhengmei Lv, Yifu He, Xiaoyi Jia, Xiaodong Jiang, Rui Wang and Wei Wang. Their work appears in journals such as Medical Oncology, Cancer Cell International, Andrologia, Scientific Reports and Gene.

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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