Dan Hu

419 citations
24 papers · 243 · h-index 9

Impact in

    • Inflammatory Biomarkers in Disease Prognosis
    • Cancer Immunotherapy and Biomarkers
    • Cancer-related molecular mechanisms research

Papers in

    • Circular RNAs in diseases 2
    • PI3K/AKT/mTOR signaling in cancer 2
    • Inflammatory Biomarkers in Disease Prognosis 2

Dan Hu

23 papers receiving 238 citations

Peers

Dan Hu
Comparison fields: 5 of 53
  • Oncology 73
  • Cancer Research 32
  • Immunology 40
  • Hepatology 10
  • Otorhinolaryngology 5
Replace Shaocheng Lyu with:
Shaocheng Lyu China
Xiaohong Xu China
Xuezhen Ma China
Maryam Bakhtiyari Iran
Xinxin Rao China
Mengyun Wang China
Rita Balsano Italy
Honggen Liu China
Yingying Luo China
Xufeng Huang Hungary
Dan Hu relative to Shaocheng Lyu China Shaocheng Lyu's profile →
Citations per field
00.5×
Shaocheng Lyu · 1×
Citations per year

Countries citing papers authored by Dan Hu

Since Specialization
Citations

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

Fields of papers citing papers by Dan Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202268
2 202135
3 202122
4 202222
5 202415
6 202314
7 202212
8 202111
9 201611
10 20226
11 20184
12 20233
13 20243
14 20233
15 20243
16 20223
17 20242
18 20241
19 20241
20 20231

About Dan Hu

Dan Hu is a scholar working on Molecular Biology, Oncology, Epidemiology, Immunology and Cancer Research, having authored 24 papers that have together received 243 indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (2 papers), Circular RNAs in diseases (2 papers), Immune cells in cancer (2 papers), Hippo pathway signaling and YAP/TAZ (2 papers), Inflammatory Biomarkers in Disease Prognosis (2 papers), PI3K/AKT/mTOR signaling in cancer (2 papers), Cancer-related molecular mechanisms research (2 papers) and Head and Neck Cancer Studies (1 paper). The work is most often cited by research in Oncology (73 citations), Cancer Research (32 citations), Immunology (40 citations), Hepatology (10 citations) and Otorhinolaryngology (5 citations). Dan Hu has collaborated with scholars based in China, South Korea and United States. Frequent co-authors include Hanchen Xu, Yujing Liu, Guang Ji, Wenjun Zhou, Ju‐Seog Lee, Ok Hee Chai, Qiqi Liu, Guodong Deng, Jian Xie and Jingxin Zhang. Their work appears in journals such as Frontiers in Oncology, Frontiers in Pharmacology, Translational Lung Cancer Research, Aging and Journal of Ethnopharmacology.

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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