Jun Shi
Impact in
- Hematology top 2%
- Hematopoietic Stem Cell Transplantation
- Acute Myeloid Leukemia Research
- Genetics top 5%
- Mesenchymal stem cell research
- Myeloproliferative Neoplasms: Diagnosis and Treatment
Papers in
- Hematology 62
- Hematopoietic Stem Cell Transplantation 30
- Acute Myeloid Leukemia Research 22
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- Epigenetics and DNA Methylation 7
- Co-authors
- Hong Wang (1 shared paper)Bei Xu (1 shared paper)Yizhou Zheng (34 shared papers)Meili Ge (29 shared papers)Xingxin Li (24 shared papers)Yingqi Shao (24 shared papers)Jinbo Huang (22 shared papers)Neng Nie (21 shared papers)
- Journals
- Blood (7 papers)Annals of Hematology (5 papers)Scientific Reports (4 papers)Leukemia (3 papers)Acta Haematologica (3 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Jun Shi
97 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 97
- Hematology 587
- Genetics 310
- Immunology 302
- Cancer Research 196
- Molecular Biology 582
Countries citing papers authored by Jun Shi
This map shows the geographic impact of Jun 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 Jun Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Shi more than expected).
Fields of papers citing papers by Jun Shi
This network shows the impact of papers produced by Jun 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 Jun Shi. The network helps show where Jun Shi may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun 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 111 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 167 | |
| 2 | 2014 | 140 | |
| 3 | 2012 | 97 | |
| 4 | 2015 | 60 | |
| 5 | 2011 | 49 | |
| 6 | 2007 | 49 | |
| 7 | 2013 | 40 | |
| 8 | 2021 | 37 | |
| 9 | 2007 | 33 | |
| 10 | 2015 | 29 | |
| 11 | 2021 | 26 | |
| 12 | 2013 | 25 | |
| 13 | 2020 | 25 | |
| 14 | 2021 | 24 | |
| 15 | 2017 | 24 | |
| 16 | 1999 | 22 | |
| 17 | 2017 | 22 | |
| 18 | 2006 | 22 | |
| 19 | 2019 | 22 | |
| 20 | 2012 | 21 |
About Jun Shi
Jun Shi is a scholar working on Hematology, Molecular Biology, Genetics, Immunology and Cancer Research, having authored 111 papers that have together received 1.4k indexed citations. Recurring topics across this work include Hematopoietic Stem Cell Transplantation (30 papers), Acute Myeloid Leukemia Research (22 papers), Mesenchymal stem cell research (10 papers), Immune Cell Function and Interaction (10 papers), T-cell and B-cell Immunology (9 papers), Erythrocyte Function and Pathophysiology (8 papers), Epigenetics and DNA Methylation (7 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (7 papers). The work is most often cited by research in Hematology (587 citations), Genetics (310 citations), Immunology (302 citations), Cancer Research (196 citations) and Molecular Biology (582 citations). Jun Shi has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Hong Wang, Bei Xu, Yizhou Zheng, Meili Ge, Xingxin Li, Yingqi Shao, Jinbo Huang, Neng Nie, Zhendong Huang and Shihong Lu. Their work appears in journals such as Blood, Annals of Hematology, Scientific Reports, Leukemia and Acta Haematologica.
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.