Leiming Xia
Impact in
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- Computational Drug Discovery Methods
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- Platelet Disorders and Treatments
Papers in
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- Protein Structure and Dynamics 4
- Oncology 9
- CAR-T cell therapy research 6
- Co-authors
- Zhen Li (4 shared papers)Yangyi Bao (7 shared papers)Qingsheng Li (5 shared papers)Lei Xu (1 shared paper)Qiao Li (3 shared papers)Fan Yang (2 shared papers)Kan Chen (2 shared papers)Ximing Xu (1 shared paper)
- Journals
- Mini-Reviews in Medicinal Chemistry (2 papers)Cancer Cell International (2 papers)Heliyon (2 papers)Cancer Research (1 paper)The Journal of Clinical Pharmacology (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Leiming Xia
32 papers receiving 300 citations
Peers
Comparison fields: 5 of 70
- Computational Theory and Mathematics 68
- Hematology 39
- Immunology 67
- Cancer Research 46
- Oncology 80
Countries citing papers authored by Leiming Xia
This map shows the geographic impact of Leiming Xia'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 Leiming Xia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leiming Xia more than expected).
Fields of papers citing papers by Leiming Xia
This network shows the impact of papers produced by Leiming Xia. 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 Leiming Xia. The network helps show where Leiming Xia may publish in the future.
Co-authors
The 25 scholars most cited alongside Leiming Xia, 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 28 | |
| 2 | 2019 | 25 | |
| 3 | 2023 | 24 | |
| 4 | 2023 | 23 | |
| 5 | 2023 | 21 | |
| 6 | 2023 | 19 | |
| 7 | 2017 | 19 | |
| 8 | 2019 | 17 | |
| 9 | 2014 | 14 | |
| 10 | 2015 | 13 | |
| 11 | 2016 | 13 | |
| 12 | 2022 | 12 | |
| 13 | 2021 | 11 | |
| 14 | 2021 | 10 | |
| 15 | 2023 | 8 | |
| 16 | 2015 | 8 | |
| 17 | 2023 | 6 | |
| 18 | 2024 | 5 | |
| 19 | 2020 | 4 | |
| 20 | 2019 | 4 |
About Leiming Xia
Leiming Xia is a scholar working on Molecular Biology, Oncology, Immunology, Hematology and Pathology and Forensic Medicine, having authored 32 papers that have together received 307 indexed citations. Recurring topics across this work include CAR-T cell therapy research (6 papers), Computational Drug Discovery Methods (5 papers), Chronic Lymphocytic Leukemia Research (4 papers), Protein Structure and Dynamics (4 papers), Immune Cell Function and Interaction (3 papers), Immunotherapy and Immune Responses (3 papers), Machine Learning in Materials Science (3 papers) and Cancer, Lipids, and Metabolism (2 papers). The work is most often cited by research in Computational Theory and Mathematics (68 citations), Hematology (39 citations), Immunology (67 citations), Cancer Research (46 citations) and Oncology (80 citations). Leiming Xia has collaborated with scholars based in China and United States. Frequent co-authors include Zhen Li, Yangyi Bao, Qingsheng Li, Lei Xu, Lei Xu, Qiao Li, Fan Yang, Kan Chen, Ximing Xu and Qibin Song. Their work appears in journals such as Mini-Reviews in Medicinal Chemistry, Cancer Cell International, Heliyon, Cancer Research and The Journal of Clinical Pharmacology.
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.