Kun He

1.8k citations
44 papers · 1.2k · h-index 19

Impact in

    • Cancer-related molecular mechanisms research
  • Oncology top 10%
    • Cancer Immunotherapy and Biomarkers

Papers in

    • RNA modifications and cancer 4
    • Single-cell and spatial transcriptomics 3
    • Immunotherapy and Immune Responses 4
    • Immune cells in cancer 4

Kun He

42 papers receiving 1.2k citations

Peers

Kun He
Comparison fields: 5 of 118
  • Cancer Research 201
  • Oncology 324
  • Immunology 243
  • Dermatology 80
  • Molecular Biology 533
Replace Domenico Angelucci with:
Domenico Angelucci Italy
Hongbo Chen China
Yabo Zhou China
Violetta Filas Poland
Simona De Summa Italy
Hua Chen China
Hiroshi Tsushima Japan
Pouria Samadi Iran
Mohamed H. Abdel‐Rahman United States
Meijuan Zhou China
Kun He relative to Domenico Angelucci Italy Domenico Angelucci's profile →
Citations per field
00.5×
Domenico Angelucci · 1×
Citations per year

Countries citing papers authored by Kun He

Since Specialization
Citations

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

Fields of papers citing papers by Kun He

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013140
2 2014112
3 2010100
4 201798
5 201655
6 201754
7 201653
8 201751
9
Liposomal doxorubicin in combination with bortezomib for relapsed or refractory multiple myeloma.
200749
10 201941
11 201940
12
Tumor associated macrophages deliver iron to tumor cells via Lcn2.
201839
13 201934
14 202032
15 201530
16 201629
17 201628
18 201827
19 202023
20 201918

About Kun He

Kun He is a scholar working on Molecular Biology, Immunology, Oncology, Hematology and Cancer Research, having authored 44 papers that have together received 1.2k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (5 papers), Cancer Immunotherapy and Biomarkers (4 papers), Immunotherapy and Immune Responses (4 papers), RNA modifications and cancer (4 papers), Immune cells in cancer (4 papers), Microgrid Control and Optimization (3 papers), Single-cell and spatial transcriptomics (3 papers) and Optimal Power Flow Distribution (3 papers). The work is most often cited by research in Cancer Research (201 citations), Oncology (324 citations), Immunology (243 citations), Dermatology (80 citations) and Molecular Biology (533 citations). Kun He has collaborated with scholars based in China, United States and Jordan. Frequent co-authors include Lisa X. Xu, Ping Liu, Richard Pazdur, Patricia Keegan, Robert Justice, Xiaoping Jiang, Hong Zhao, Sarah Pope Miksinski, Xiaoyuan Xu and Zheng Yan. Their work appears in journals such as Clinical Cancer Research, International Journal of Hyperthermia, Cell Death and Disease, Frontiers in Oncology and Biochemical and Biophysical Research Communications.

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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