Runxia Gu
Impact in
- Hematology top 10%
- Acute Myeloid Leukemia Research
-
- CAR-T cell therapy research
- Cancer Immunotherapy and Biomarkers
- Cancer Cells and Metastasis
Papers in
- Hematology 26
- Acute Myeloid Leukemia Research 24
- Oncology 15
- CAR-T cell therapy research 12
- Cancer-related Molecular Pathways 2
- Co-authors
- Hui Wei (23 shared papers)Xue Wen Yang (1 shared paper)Jianxiang Wang (35 shared papers)Gang Wu (3 shared papers)Dapeng Li (2 shared papers)Junli Liu (3 shared papers)Foad Katirai (1 shared paper)Wenqian Cai (1 shared paper)
- Journals
- Blood (3 papers)British Journal of Haematology (3 papers)Haematologica (3 papers)Experimental Hematology and Oncology (2 papers)Journal of Hematology & Oncology (2 papers)
- Partner nations
- ChinaUnited States
In The Last Decade
Runxia Gu
50 papers receiving 579 citations
Peers
Comparison fields: 5 of 50
- Hematology 137
- Oncology 179
- Endocrinology, Diabetes and Metabolism 81
- Immunology 61
- Cancer Research 24
Countries citing papers authored by Runxia Gu
This map shows the geographic impact of Runxia Gu'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 Runxia Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Runxia Gu more than expected).
Fields of papers citing papers by Runxia Gu
This network shows the impact of papers produced by Runxia Gu. 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 Runxia Gu. The network helps show where Runxia Gu may publish in the future.
Co-authors
The 25 scholars most cited alongside Runxia Gu, 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 55 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 105 | |
| 2 | 2020 | 69 | |
| 3 | 2018 | 34 | |
| 4 | 2018 | 32 | |
| 5 | 2013 | 28 | |
| 6 | 2020 | 28 | |
| 7 | 2020 | 27 | |
| 8 | 2017 | 25 | |
| 9 | 2024 | 21 | |
| 10 | 2015 | 18 | |
| 11 | 2012 | 14 | |
| 12 | 2015 | 14 | |
| 13 | 2024 | 13 | |
| 14 | TLR3 correlated with cervical lymph node metastasis in patients with papillary thyroid cancer. | 2014 | 12 |
| 15 | 2021 | 11 | |
| 16 | 2024 | 9 | |
| 17 | 2017 | 8 | |
| 18 | 2020 | 8 | |
| 19 | 2021 | 8 | |
| 20 | 2023 | 8 |
About Runxia Gu
Runxia Gu is a scholar working on Hematology, Oncology, Public Health, Environmental and Occupational Health, Cancer Research and Molecular Biology, having authored 55 papers that have together received 592 indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (24 papers), CAR-T cell therapy research (12 papers), Acute Lymphoblastic Leukemia research (8 papers), Cancer-related Molecular Pathways (2 papers), Angiogenesis and VEGF in Cancer (2 papers), Lung Cancer Treatments and Mutations (1 paper), Cancer, Hypoxia, and Metabolism (1 paper) and Antifungal resistance and susceptibility (1 paper). The work is most often cited by research in Hematology (137 citations), Oncology (179 citations), Endocrinology, Diabetes and Metabolism (81 citations), Immunology (61 citations) and Cancer Research (24 citations). Runxia Gu has collaborated with scholars based in China and United States. Frequent co-authors include Hui Wei, Xue Wen Yang, Jianxiang Wang, Gang Wu, Dapeng Li, Junli Liu, Foad Katirai, Wenqian Cai, Bo Huang and Huafeng Zhang. Their work appears in journals such as Blood, British Journal of Haematology, Haematologica, Experimental Hematology and Oncology and Journal of Hematology & Oncology.
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.