Haiying Que
Impact in
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- Immune cells in cancer
- Immunotherapy and Immune Responses
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- Advanced biosensing and bioanalysis techniques
- CRISPR and Genetic Engineering
- RNA Interference and Gene Delivery
Papers in
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- Advanced biosensing and bioanalysis techniques 7
- RNA Interference and Gene Delivery 5
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- Biosensors and Analytical Detection 6
- Co-authors
- Tianxia Lan (6 shared papers)Xiawei Wei (2 shared papers)Xiaohe Tian (1 shared paper)Yurong Yan (4 shared papers)Decai Zhang (3 shared papers)Xiaoxue Cheng (1 shared paper)Shijia Ding (1 shared paper)Wei Cheng (1 shared paper)
- Journals
- Signal Transduction and Targeted Therapy (3 papers)Molecular Cancer (2 papers)Sensors and Actuators B Chemical (2 papers)RSC Advances (2 papers)Biosensors and Bioelectronics (2 papers)
- Partner nations
- China
In The Last Decade
Haiying Que
22 papers receiving 821 citations
Haiying Que's Hit Papers
Peers
Comparison fields: 5 of 82
- Immunology 176
- Molecular Biology 432
- Drug Discovery 1
- Neurology 75
- Infectious Diseases 87
Countries citing papers authored by Haiying Que
This map shows the geographic impact of Haiying Que'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 Haiying Que with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haiying Que more than expected).
Fields of papers citing papers by Haiying Que
This network shows the impact of papers produced by Haiying Que. 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 Haiying Que. The network helps show where Haiying Que may publish in the future.
Co-authors
The 25 scholars most cited alongside Haiying Que, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Tumor-associated neutrophils and neutrophil-targeted cancer therapies Hit paper breakdown → | 2022 | 206 |
| 2 | 2020 | 205 | |
| 3 | 2021 | 91 | |
| 4 | 2021 | 39 | |
| 5 | 2022 | 35 | |
| 6 | 2019 | 34 | |
| 7 | 2019 | 27 | |
| 8 | 2019 | 27 | |
| 9 | 2021 | 26 | |
| 10 | 2025 | 25 | |
| 11 | 2022 | 22 | |
| 12 | 2022 | 21 | |
| 13 | 2018 | 17 | |
| 14 | 2019 | 13 | |
| 15 | 2025 | 10 | |
| 16 | 2019 | 7 | |
| 17 | 2022 | 6 | |
| 18 | 2024 | 5 | |
| 19 | 2024 | 5 | |
| 20 | 2024 | 5 |
About Haiying Que
Haiying Que is a scholar working on Molecular Biology, Biomedical Engineering, Infectious Diseases, Immunology and Neurology, having authored 22 papers that have together received 828 indexed citations. Recurring topics across this work include Advanced biosensing and bioanalysis techniques (7 papers), Immunotherapy and Immune Responses (6 papers), Biosensors and Analytical Detection (6 papers), SARS-CoV-2 and COVID-19 Research (6 papers), RNA Interference and Gene Delivery (5 papers), Long-Term Effects of COVID-19 (3 papers), COVID-19 Clinical Research Studies (3 papers) and Immune Response and Inflammation (3 papers). The work is most often cited by research in Immunology (176 citations), Molecular Biology (432 citations), Drug Discovery (1 citation), Neurology (75 citations) and Infectious Diseases (87 citations). Haiying Que has collaborated with scholars based in China. Frequent co-authors include Tianxia Lan, Xiawei Wei, Xiaohe Tian, Yurong Yan, Decai Zhang, Xiaoxue Cheng, Shijia Ding, Wei Cheng, Tiantian Yang and Xiuming Zhang. Their work appears in journals such as Signal Transduction and Targeted Therapy, Molecular Cancer, Sensors and Actuators B Chemical, RSC Advances and Biosensors and Bioelectronics.
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.