Kesi Shi
Impact in
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- Spinal Cord Injury Research
- Spine and Intervertebral Disc Pathology
- Developmental Neuroscience top 10%
- Neurogenesis and neuroplasticity mechanisms
Papers in
-
- Spinal Cord Injury Research 8
- Spine and Intervertebral Disc Pathology 7
-
- Pluripotent Stem Cells Research 3
- Extracellular vesicles in disease 2
- Co-authors
- Fangcai Li (18 shared papers)Kaishun Xia (19 shared papers)Qixin Chen (18 shared papers)Chenggui Wang (13 shared papers)Feng Cheng (13 shared papers)Jingkai Wang (15 shared papers)Chengzhen Liang (18 shared papers)Liwei Ying (10 shared papers)
- Journals
- Cell Death and Disease (3 papers)Current Stem Cell Research & Therapy (3 papers)Bioactive Materials (2 papers)Molecular Therapy (1 paper)Bioengineering & Translational Medicine (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Kesi Shi
26 papers receiving 840 citations
Peers
Comparison fields: 5 of 83
- Pathology and Forensic Medicine 364
- Developmental Neuroscience 64
- Cellular and Molecular Neuroscience 231
- Neurology 63
- Pharmacology 120
Countries citing papers authored by Kesi Shi
This map shows the geographic impact of Kesi 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 Kesi Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kesi Shi more than expected).
Fields of papers citing papers by Kesi Shi
This network shows the impact of papers produced by Kesi 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 Kesi Shi. The network helps show where Kesi Shi may publish in the future.
Co-authors
The 25 scholars most cited alongside Kesi 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 139 | |
| 2 | 2021 | 107 | |
| 3 | 2020 | 86 | |
| 4 | 2018 | 85 | |
| 5 | 2021 | 80 | |
| 6 | 2017 | 76 | |
| 7 | 2020 | 57 | |
| 8 | 2022 | 29 | |
| 9 | 2023 | 28 | |
| 10 | 2017 | 28 | |
| 11 | 2020 | 25 | |
| 12 | 2020 | 18 | |
| 13 | 2022 | 18 | |
| 14 | 2020 | 11 | |
| 15 | 2019 | 10 | |
| 16 | 2023 | 8 | |
| 17 | 2023 | 7 | |
| 18 | 2024 | 7 | |
| 19 | 2023 | 6 | |
| 20 | 2024 | 6 |
About Kesi Shi
Kesi Shi is a scholar working on Pathology and Forensic Medicine, Molecular Biology, Cellular and Molecular Neuroscience, Pharmacology and Surgery, having authored 28 papers that have together received 845 indexed citations. Recurring topics across this work include Spinal Cord Injury Research (8 papers), Spine and Intervertebral Disc Pathology (7 papers), Nerve injury and regeneration (7 papers), Musculoskeletal pain and rehabilitation (4 papers), Pluripotent Stem Cells Research (3 papers), Mesenchymal stem cell research (2 papers), Neuropeptides and Animal Physiology (2 papers) and Extracellular vesicles in disease (2 papers). The work is most often cited by research in Pathology and Forensic Medicine (364 citations), Developmental Neuroscience (64 citations), Cellular and Molecular Neuroscience (231 citations), Neurology (63 citations) and Pharmacology (120 citations). Kesi Shi has collaborated with scholars based in China and United States. Frequent co-authors include Fangcai Li, Kaishun Xia, Qixin Chen, Chenggui Wang, Feng Cheng, Jingkai Wang, Chengzhen Liang, Liwei Ying, Xiangyang Wang and Biao Yang. Their work appears in journals such as Cell Death and Disease, Current Stem Cell Research & Therapy, Bioactive Materials, Molecular Therapy and Bioengineering & Translational Medicine.
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.