Xiaolei Pei
Impact in
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- Chemokine receptors and signaling
- CAR-T cell therapy research
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- Virus-based gene therapy research
Papers in
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- RNA Interference and Gene Delivery 4
- Extracellular vesicles in disease 3
- Viral Infectious Diseases and Gene Expression in Insects 3
- Genetics 10
- Virus-based gene therapy research 10
- Co-authors
- Ying Wang (5 shared papers)Dalong Ma (4 shared papers)Yingmei Zhang (4 shared papers)R. Jude Samulski (4 shared papers)Chengwen Li (4 shared papers)Xiaojing Chen (3 shared papers)David A. Gerber (3 shared papers)Xiaoning Mo (4 shared papers)
- Journals
- Blood (3 papers)Molecular Therapy — Methods & Clinical Development (2 papers)Frontiers in Immunology (2 papers)Nature Communications (1 paper)Signal Transduction and Targeted Therapy (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Xiaolei Pei
25 papers receiving 335 citations
Peers
Comparison fields: 5 of 70
- Oncology 88
- Genetics 87
- Immunology 57
- Cancer Research 37
- Molecular Biology 171
Countries citing papers authored by Xiaolei Pei
This map shows the geographic impact of Xiaolei Pei'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 Xiaolei Pei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaolei Pei more than expected).
Fields of papers citing papers by Xiaolei Pei
This network shows the impact of papers produced by Xiaolei Pei. 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 Xiaolei Pei. The network helps show where Xiaolei Pei may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaolei Pei, 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 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 50 | |
| 2 | 2016 | 35 | |
| 3 | 2014 | 31 | |
| 4 | 2018 | 28 | |
| 5 | 2020 | 25 | |
| 6 | 2018 | 20 | |
| 7 | 2019 | 18 | |
| 8 | 2017 | 17 | |
| 9 | Who is hematopoietic stem cell: CD34+ or CD34-? | 1999 | 16 |
| 10 | 2022 | 14 | |
| 11 | 2015 | 14 | |
| 12 | 2023 | 13 | |
| 13 | 2021 | 13 | |
| 14 | 2024 | 13 | |
| 15 | 2019 | 6 | |
| 16 | 2024 | 5 | |
| 17 | 2022 | 4 | |
| 18 | 2022 | 4 | |
| 19 | 2019 | 3 | |
| 20 | 2024 | 2 |
About Xiaolei Pei
Xiaolei Pei is a scholar working on Molecular Biology, Genetics, Oncology, Immunology and Hematology, having authored 33 papers that have together received 338 indexed citations. Recurring topics across this work include Virus-based gene therapy research (10 papers), CAR-T cell therapy research (5 papers), RNA Interference and Gene Delivery (4 papers), Immunotherapy and Immune Responses (4 papers), Immune cells in cancer (3 papers), Extracellular vesicles in disease (3 papers), Viral Infectious Diseases and Gene Expression in Insects (3 papers) and Chemokine receptors and signaling (3 papers). The work is most often cited by research in Oncology (88 citations), Genetics (87 citations), Immunology (57 citations), Cancer Research (37 citations) and Molecular Biology (171 citations). Xiaolei Pei has collaborated with scholars based in China and United States. Frequent co-authors include Ying Wang, Dalong Ma, Yingmei Zhang, R. Jude Samulski, Chengwen Li, Xiaojing Chen, David A. Gerber, Xiaoning Mo, John Blenis and Michelle C. Mendoza. Their work appears in journals such as Blood, Molecular Therapy — Methods & Clinical Development, Frontiers in Immunology, Nature Communications and Signal Transduction and Targeted Therapy.
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.