Haide Chen
Impact in
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- Single-cell and spatial transcriptomics
- Pluripotent Stem Cells Research
- CRISPR and Genetic Engineering
- Gene expression and cancer classification
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- Immune cells in cancer
- Immune Cell Function and Interaction
Papers in
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- Single-cell and spatial transcriptomics 16
- Pluripotent Stem Cells Research 8
- CRISPR and Genetic Engineering 7
- RNA Research and Splicing 3
- Genetics 6
- Animal Genetics and Reproduction 3
- Co-authors
- Guoji Guo (17 shared papers)Fang Ye (4 shared papers)Guo‐Cheng Yuan (3 shared papers)Daphne Tsoucas (1 shared paper)Rui Dong (1 shared paper)Qian Zhu (1 shared paper)Xiaoping Han (10 shared papers)Lijiang Fei (7 shared papers)
- Journals
- Cell Discovery (3 papers)Animal Reproduction Science (2 papers)Brazilian Journal of Medical and Biological Research (1 paper)Cellular and Molecular Immunology (1 paper)Scientific Reports (1 paper)
- Partner nations
- ChinaUnited StatesIndia
In The Last Decade
Haide Chen
27 papers receiving 852 citations
Peers
Comparison fields: 5 of 93
- Molecular Biology 650
- Immunology 191
- Cancer Research 131
- Aging 13
- Biophysics 39
Countries citing papers authored by Haide Chen
This map shows the geographic impact of Haide Chen'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 Haide Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haide Chen more than expected).
Fields of papers citing papers by Haide Chen
This network shows the impact of papers produced by Haide Chen. 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 Haide Chen. The network helps show where Haide Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Haide Chen, 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 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 156 | |
| 2 | 2019 | 138 | |
| 3 | 2018 | 76 | |
| 4 | 2013 | 59 | |
| 5 | 2022 | 55 | |
| 6 | 2021 | 53 | |
| 7 | 2021 | 48 | |
| 8 | 2015 | 36 | |
| 9 | 2014 | 33 | |
| 10 | 2022 | 29 | |
| 11 | 2012 | 28 | |
| 12 | 2016 | 27 | |
| 13 | 2019 | 23 | |
| 14 | 2016 | 20 | |
| 15 | 2018 | 12 | |
| 16 | 2013 | 12 | |
| 17 | 2018 | 11 | |
| 18 | 2020 | 10 | |
| 19 | 2021 | 9 | |
| 20 | 2022 | 6 |
About Haide Chen
Haide Chen is a scholar working on Molecular Biology, Genetics, Immunology, Surgery and Oncology, having authored 30 papers that have together received 862 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (16 papers), Pluripotent Stem Cells Research (8 papers), CRISPR and Genetic Engineering (7 papers), Cell Image Analysis Techniques (4 papers), Immune cells in cancer (4 papers), RNA Research and Splicing (3 papers), T-cell and B-cell Immunology (3 papers) and Animal Genetics and Reproduction (3 papers). The work is most often cited by research in Molecular Biology (650 citations), Immunology (191 citations), Cancer Research (131 citations), Aging (13 citations) and Biophysics (39 citations). Haide Chen has collaborated with scholars based in China, United States and India. Frequent co-authors include Guoji Guo, Fang Ye, Guo‐Cheng Yuan, Daphne Tsoucas, Rui Dong, Qian Zhu, Xiaoping Han, Lijiang Fei, Lei Xiao and Chun Cui. Their work appears in journals such as Cell Discovery, Animal Reproduction Science, Brazilian Journal of Medical and Biological Research, Cellular and Molecular Immunology and Scientific Reports.
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.