Xiaolan Shi
Impact in
- Oncology top 10%
- CAR-T cell therapy research
- Hematology top 10%
- Multiple Myeloma Research and Treatments
Papers in
- Hematology 17
- Multiple Myeloma Research and Treatments 12
- Hematopoietic Stem Cell Transplantation 6
- Acute Myeloid Leukemia Research 4
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- Protein Degradation and Inhibitors 4
- Co-authors
- Lingzhi Yan (17 shared papers)Chengcheng Fu (16 shared papers)Long Zhao (2 shared papers)Liqing Kang (5 shared papers)Cuicui Liu (2 shared papers)Jingjing Shang (13 shared papers)Song Jin (13 shared papers)Li Wang (1 shared paper)
- Journals
- Blood (13 papers)The Science of The Total Environment (1 paper)Journal of Personalized Medicine (1 paper)Sustainability (1 paper)Journal of Clinical Medicine (1 paper)
- Partner nations
- ChinaUnited KingdomBangladesh
In The Last Decade
Xiaolan Shi
39 papers receiving 492 citations
Peers
Comparison fields: 5 of 85
- Oncology 242
- Hematology 91
- Immunology 92
- Molecular Biology 209
- Cancer Research 43
Countries citing papers authored by Xiaolan Shi
This map shows the geographic impact of Xiaolan Shi'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 Xiaolan Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaolan Shi more than expected).
Fields of papers citing papers by Xiaolan Shi
This network shows the impact of papers produced by Xiaolan Shi. 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 Xiaolan Shi. The network helps show where Xiaolan Shi may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaolan Shi, 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 43 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 54 | |
| 2 | 2014 | 51 | |
| 3 | 2018 | 49 | |
| 4 | 2020 | 44 | |
| 5 | 2013 | 28 | |
| 6 | 2017 | 26 | |
| 7 | 2022 | 26 | |
| 8 | 2024 | 20 | |
| 9 | 2023 | 20 | |
| 10 | 2021 | 17 | |
| 11 | 2019 | 16 | |
| 12 | 2023 | 16 | |
| 13 | 2019 | 16 | |
| 14 | 2023 | 14 | |
| 15 | 2019 | 10 | |
| 16 | 2021 | 9 | |
| 17 | 2015 | 9 | |
| 18 | 2024 | 8 | |
| 19 | 2020 | 8 | |
| 20 | 2021 | 7 |
About Xiaolan Shi
Xiaolan Shi is a scholar working on Hematology, Molecular Biology, Oncology, Immunology and Pathology and Forensic Medicine, having authored 43 papers that have together received 496 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (12 papers), CAR-T cell therapy research (8 papers), Hematopoietic Stem Cell Transplantation (6 papers), Protein Degradation and Inhibitors (4 papers), Acute Myeloid Leukemia Research (4 papers), Immune Cell Function and Interaction (3 papers), Biosimilars and Bioanalytical Methods (3 papers) and Atmospheric and Environmental Gas Dynamics (2 papers). The work is most often cited by research in Oncology (242 citations), Hematology (91 citations), Immunology (92 citations), Molecular Biology (209 citations) and Cancer Research (43 citations). Xiaolan Shi has collaborated with scholars based in China, United Kingdom and Bangladesh. Frequent co-authors include Lingzhi Yan, Chengcheng Fu, Long Zhao, Liqing Kang, Cuicui Liu, Jingjing Shang, Song Jin, Li Wang, Ning Wang and Jin Zhou. Their work appears in journals such as Blood, The Science of The Total Environment, Journal of Personalized Medicine, Sustainability and Journal of Clinical Medicine.
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.