Can Shi
Impact in
- Hematology top 2%
- Platelet Disorders and Treatments
- Immunology and Allergy top 5%
- Cell Adhesion Molecules Research
Papers in
-
- Circular RNAs in diseases 5
- FOXO transcription factor regulation 2
- Immunology 12
- Immune Response and Inflammation 7
- T-cell and B-cell Immunology 3
- Co-authors
- Daniel I. Simon (18 shared papers)Masashi Sakuma (9 shared papers)Yunmei Wang (9 shared papers)Kevin Croce (7 shared papers)Huiyun Gao (6 shared papers)Alexandre C. Zago (4 shared papers)Peter Libby (2 shared papers)Zhiping Chen (3 shared papers)
- Journals
- Cell Research (3 papers)Journal of Clinical Investigation (3 papers)Circulation (3 papers)Arteriosclerosis Thrombosis and Vascular Biology (3 papers)Blood (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Can Shi
42 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 99
- Hematology 322
- Immunology and Allergy 168
- Immunology 582
- Cancer Research 328
- Internal Medicine 57
Countries citing papers authored by Can Shi
This map shows the geographic impact of Can 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 Can Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Can Shi more than expected).
Fields of papers citing papers by Can Shi
This network shows the impact of papers produced by Can 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 Can Shi. The network helps show where Can Shi may publish in the future.
Co-authors
The 25 scholars most cited alongside Can 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 43 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 241 | |
| 2 | 2009 | 203 | |
| 3 | 2005 | 146 | |
| 4 | 2017 | 132 | |
| 5 | 2008 | 106 | |
| 6 | 2014 | 106 | |
| 7 | 2018 | 87 | |
| 8 | 2004 | 84 | |
| 9 | 2008 | 82 | |
| 10 | 2004 | 82 | |
| 11 | 2004 | 72 | |
| 12 | 2004 | 67 | |
| 13 | 2001 | 59 | |
| 14 | 2011 | 51 | |
| 15 | 2015 | 48 | |
| 16 | The long noncoding RNA LINC00473, a target of microRNA 34a, promotes tumorigenesis by inhibiting ILF2 degradation in cervical cancer. | 2017 | 46 |
| 17 | 2017 | 43 | |
| 18 | 2019 | 42 | |
| 19 | 2006 | 37 | |
| 20 | 2001 | 35 |
About Can Shi
Can Shi is a scholar working on Molecular Biology, Immunology, Cancer Research, Immunology and Allergy and Oncology, having authored 43 papers that have together received 2.1k indexed citations. Recurring topics across this work include Immune Response and Inflammation (7 papers), Cell Adhesion Molecules Research (6 papers), MicroRNA in disease regulation (6 papers), Cancer-related molecular mechanisms research (6 papers), Circular RNAs in diseases (5 papers), T-cell and B-cell Immunology (3 papers), Endometriosis Research and Treatment (2 papers) and FOXO transcription factor regulation (2 papers). The work is most often cited by research in Hematology (322 citations), Immunology and Allergy (168 citations), Immunology (582 citations), Cancer Research (328 citations) and Internal Medicine (57 citations). Can Shi has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Daniel I. Simon, Masashi Sakuma, Yunmei Wang, Kevin Croce, Huiyun Gao, Alexandre C. Zago, Peter Libby, Zhiping Chen, Zhiping Chen and Yue Dai. Their work appears in journals such as Cell Research, Journal of Clinical Investigation, Circulation, Arteriosclerosis Thrombosis and Vascular Biology and Blood.
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.