Huiying Han
Impact in
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Molecular Biology top 10%
- Protein Degradation and Inhibitors
- Extracellular vesicles in disease
- RNA modifications and cancer
- Ubiquitin and proteasome pathways
- Circular RNAs in diseases
Papers in
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- Cancer-related molecular mechanisms research 6
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- Multiple Myeloma Research and Treatments 6
- Co-authors
- Sha SongWenzhuo ZhuangBing-Zong LiChenao QianSarki A. AbdulkadirVinay SagarMihai I. TruicaHongxia Xu
- Journals
- Cancer Research (3 papers)Blood (3 papers)Clinical Cancer Research (2 papers)Molecular Pharmaceutics (2 papers)Journal of Molecular Biology (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Huiying Han
29 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Cancer Research 402
- Molecular Biology 907
- Oncology 290
- Hematology 118
- Immunology 117
Countries citing papers authored by Huiying Han
This map shows the geographic impact of Huiying Han'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 Huiying Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Huiying Han more than expected).
Fields of papers citing papers by Huiying Han
This network shows the impact of papers produced by Huiying Han. 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 Huiying Han. The network helps show where Huiying Han may publish in the future.
Co-authors
The 25 scholars most cited alongside Huiying Han, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2022 | 37 | |
| 3 | 2022 | 24 | |
| 4 | 2021 | 41 | |
| 5 | 2021 | 35 | |
| 6 | 2021 | 16 | |
| 7 | 2020 | 32 | |
| 8 | 2020 | 136 | |
| 9 | 2019 | 106 | |
| 10 | Small-Molecule MYC Inhibitors Suppress Tumor Growth and Enhance Immunotherapy Hit paper breakdown → | 2019 | 302 |
| 11 | 2019 | 44 | |
| 12 | 2018 | 34 | |
| 13 | 2018 | 32 | |
| 14 | 2018 | 10 | |
| 15 | 2018 | 122 | |
| 16 | 2018 | 20 | |
| 17 | 2008 | 12 | |
| 18 | 2008 | 20 | |
| 19 | 2008 | 35 | |
| 20 | C-glycosylfavones and aromatic glycosides from Campylotropis hirtella (Franch.) Schindl. | 2007 | 16 |
About Huiying Han
Huiying Han is a scholar working on Cancer Research, Hematology, Immunology and Allergy, Molecular Biology and Developmental Neuroscience, having authored 31 papers that have together received 1.3k indexed citations. Recurring topics across this work include Protein Degradation and Inhibitors (9 papers), Ubiquitin and proteasome pathways (7 papers), Multiple Myeloma Research and Treatments (6 papers), Cancer-related molecular mechanisms research (6 papers), Phytochemistry and Biological Activities (4 papers), Peptidase Inhibition and Analysis (4 papers), Natural product bioactivities and synthesis (3 papers) and RNA modifications and cancer (3 papers). The work is most often cited by research in Cancer Research (402 citations), Molecular Biology (907 citations), Oncology (290 citations), Hematology (118 citations) and Immunology (117 citations). Huiying Han has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Sha Song, Wenzhuo Zhuang, Bing-Zong Li, Chenao Qian, Sarki A. Abdulkadir, Vinay Sagar, Mihai I. Truica, Hongxia Xu, Kenji Unno and Rajita Vatapalli. Their work appears in journals such as Cancer Research, Blood, Clinical Cancer Research, Molecular Pharmaceutics and Journal of Molecular Biology.
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.