Xiaolan Shi
Impact in
- Oncology top 10%
- CAR-T cell therapy research
- Hematology top 10%
- Multiple Myeloma Research and Treatments
Papers in
- Hematology 20
- Multiple Myeloma Research and Treatments 15
- Hematopoietic Stem Cell Transplantation 6
- Acute Myeloid Leukemia Research 4
- Oncology 18
- CAR-T cell therapy research 11
- Co-authors
- Lingzhi Yan (21 shared papers)Chengcheng Fu (19 shared papers)Song Jin (16 shared papers)Jingjing Shang (17 shared papers)Guanghua Chen (6 shared papers)Liqing Kang (7 shared papers)Depei Wu (17 shared papers)Weiqin Yao (13 shared papers)
- Journals
- Blood (15 papers)Molecular Immunology (1 paper)Frontiers in Oncology (1 paper)The American Journal of Surgical Pathology (1 paper)Environmental Pollution (1 paper)
- Partner nations
- ChinaHong KongUnited Kingdom
In The Last Decade
Xiaolan Shi
42 papers receiving 597 citations
Peers
Comparison fields: 5 of 77
- Oncology 299
- Hematology 105
- Immunology 92
- Molecular Biology 219
- Cancer Research 36
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 47 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 66 | |
| 2 | 2014 | 55 | |
| 3 | 2019 | 54 | |
| 4 | 2018 | 49 | |
| 5 | 2020 | 46 | |
| 6 | 2022 | 29 | |
| 7 | 2013 | 28 | |
| 8 | 2017 | 26 | |
| 9 | 2024 | 26 | |
| 10 | 2023 | 20 | |
| 11 | 2021 | 18 | |
| 12 | 2023 | 18 | |
| 13 | 2019 | 17 | |
| 14 | 2023 | 16 | |
| 15 | 2019 | 16 | |
| 16 | 2019 | 10 | |
| 17 | 2015 | 10 | |
| 18 | 2021 | 10 | |
| 19 | 2022 | 10 | |
| 20 | 2020 | 8 |
About Xiaolan Shi
Xiaolan Shi is a scholar working on Hematology, Oncology, Molecular Biology, Immunology and Pathology and Forensic Medicine, having authored 47 papers that have together received 600 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (15 papers), CAR-T cell therapy research (11 papers), Hematopoietic Stem Cell Transplantation (6 papers), Protein Degradation and Inhibitors (4 papers), Acute Myeloid Leukemia Research (4 papers), Biosimilars and Bioanalytical Methods (3 papers), Liver Disease Diagnosis and Treatment (2 papers) and Atmospheric chemistry and aerosols (2 papers). The work is most often cited by research in Oncology (299 citations), Hematology (105 citations), Immunology (92 citations), Molecular Biology (219 citations) and Cancer Research (36 citations). Xiaolan Shi has collaborated with scholars based in China, Hong Kong and United Kingdom. Frequent co-authors include Lingzhi Yan, Chengcheng Fu, Song Jin, Jingjing Shang, Guanghua Chen, Liqing Kang, Depei Wu, Weiqin Yao, Lei Yu and Jin Zhou. Their work appears in journals such as Blood, Molecular Immunology, Frontiers in Oncology, The American Journal of Surgical Pathology and Environmental Pollution.
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.