Sujun Gao
Impact in
- Hematology top 2%
- Acute Myeloid Leukemia Research
- Chronic Myeloid Leukemia Treatments
- Genetics top 5%
- Chronic Lymphocytic Leukemia Research
- Myeloproliferative Neoplasms: Diagnosis and Treatment
Papers in
- Hematology 49
- Acute Myeloid Leukemia Research 33
- Chronic Myeloid Leukemia Treatments 17
- Hematopoietic Stem Cell Transplantation 6
- Genetics 29
- Myeloproliferative Neoplasms: Diagnosis and Treatment 17
- Chronic Lymphocytic Leukemia Research 10
- Co-authors
- Long Su (25 shared papers)Yehui Tan (21 shared papers)Siqing Wang (5 shared papers)Yuxue Jiang (5 shared papers)Jintong Chen (5 shared papers)Yinghua Zhao (4 shared papers)Qing Yi (4 shared papers)Jane Huang (2 shared papers)
- Journals
- Blood (6 papers)Journal of Clinical Oncology (6 papers)Medicine (5 papers)Annals of Hematology (5 papers)Oncotarget (4 papers)
- Partner nations
- ChinaUnited StatesSwitzerland
In The Last Decade
Sujun Gao
84 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 85
- Hematology 408
- Genetics 258
- Immunology 266
- Pathology and Forensic Medicine 175
- Oncology 187
Countries citing papers authored by Sujun Gao
This map shows the geographic impact of Sujun Gao'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 Sujun Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sujun Gao more than expected).
Fields of papers citing papers by Sujun Gao
This network shows the impact of papers produced by Sujun Gao. 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 Sujun Gao. The network helps show where Sujun Gao may publish in the future.
Co-authors
The 25 scholars most cited alongside Sujun Gao, 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 94 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 122 | |
| 2 | 2020 | 97 | |
| 3 | 2018 | 61 | |
| 4 | 2019 | 51 | |
| 5 | 2004 | 50 | |
| 6 | 2018 | 45 | |
| 7 | 2018 | 36 | |
| 8 | 2020 | 31 | |
| 9 | 2018 | 30 | |
| 10 | 2015 | 29 | |
| 11 | 2018 | 28 | |
| 12 | 2022 | 27 | |
| 13 | 2023 | 24 | |
| 14 | 2019 | 24 | |
| 15 | 2021 | 21 | |
| 16 | 2016 | 20 | |
| 17 | 2016 | 20 | |
| 18 | 2023 | 18 | |
| 19 | 2022 | 18 | |
| 20 | 2018 | 18 |
About Sujun Gao
Sujun Gao is a scholar working on Hematology, Genetics, Molecular Biology, Immunology and Pathology and Forensic Medicine, having authored 94 papers that have together received 1.1k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (33 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (17 papers), Chronic Myeloid Leukemia Treatments (17 papers), Chronic Lymphocytic Leukemia Research (10 papers), Lymphoma Diagnosis and Treatment (8 papers), Histone Deacetylase Inhibitors Research (7 papers), Hematopoietic Stem Cell Transplantation (6 papers) and Protein Degradation and Inhibitors (6 papers). The work is most often cited by research in Hematology (408 citations), Genetics (258 citations), Immunology (266 citations), Pathology and Forensic Medicine (175 citations) and Oncology (187 citations). Sujun Gao has collaborated with scholars based in China, United States and Switzerland. Frequent co-authors include Long Su, Yehui Tan, Siqing Wang, Yuxue Jiang, Jintong Chen, Yinghua Zhao, Qing Yi, Jane Huang, Jianfeng Zhou and Haiyi Guo. Their work appears in journals such as Blood, Journal of Clinical Oncology, Medicine, Annals of Hematology and Oncotarget.
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.