Si Wang
Impact in
- Aging top 0.5%
- Genetics, Aging, and Longevity in Model Organisms
- Geriatrics and Gerontology top 2%
Papers in ⓘ
- Aging 11
- Genetics, Aging, and Longevity in Model Organisms 11
- Co-authors
- Jing Qu (61 shared papers)Guang‐Hui Liu (59 shared papers)Weiqi Zhang (54 shared papers)Moshi Song (21 shared papers)Juan Carlos Izpisúa Belmonte (30 shared papers)Zunpeng Liu (18 shared papers)Shuai Ma (27 shared papers)Piu Chan (9 shared papers)
- Journals
- Protein & Cell (25 papers)Nucleic Acids Research (8 papers)Cell stem cell (3 papers)Nature Aging (3 papers)Advanced Materials Interfaces (2 papers)
- Partner nations
- ChinaUnited StatesIndia
In The Last Decade
Si Wang
122 papers receiving 4.2k citations
Hit Papers
Peers
Comparison fields: 5 of 160
- Aging 347
- Geriatrics and Gerontology 168
- Cancer Research 637
- Molecular Biology 2.5k
- Physiology 582
Countries citing papers authored by Si Wang
This map shows the geographic impact of Si Wang'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 Si Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Si Wang more than expected).
Fields of papers citing papers by Si Wang
This network shows the impact of papers produced by Si Wang. 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 Si Wang. The network helps show where Si Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Si Wang, 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 127 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 316 | |
| 2 | 2020 | 231 | |
| 3 | 2020 | 208 | |
| 4 | Exosomes from adipose-derived stem cells regulate M1/M2 macrophage phenotypic polarization to promote bone healing via miR-451a/MIF Hit paper breakdown → | 2022 | 134 |
| 5 | 2020 | 131 | |
| 6 | 2019 | 123 | |
| 7 | 2021 | 119 | |
| 8 | 2022 | 112 | |
| 9 | 2021 | 108 | |
| 10 | 2020 | 105 | |
| 11 | 2022 | 102 | |
| 12 | 2020 | 95 | |
| 13 | 2017 | 94 | |
| 14 | 2022 | 83 | |
| 15 | 2016 | 81 | |
| 16 | 2019 | 80 | |
| 17 | 2020 | 76 | |
| 18 | 2021 | 72 | |
| 19 | 2014 | 66 | |
| 20 | 2020 | 65 |
About Si Wang
Si Wang is a scholar working on Aging, Geriatrics and Gerontology, Molecular Biology, Horticulture and Cancer Research, having authored 127 papers that have together received 4.3k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (12 papers), Pluripotent Stem Cells Research (12 papers), Genetics, Aging, and Longevity in Model Organisms (11 papers), CRISPR and Genetic Engineering (9 papers), Epigenetics and DNA Methylation (9 papers), Telomeres, Telomerase, and Senescence (9 papers), MicroRNA in disease regulation (8 papers) and Circular RNAs in diseases (5 papers). The work is most often cited by research in Aging (347 citations), Geriatrics and Gerontology (168 citations), Cancer Research (637 citations), Molecular Biology (2.5k citations) and Physiology (582 citations). Si Wang has collaborated with scholars based in China, United States and India. Frequent co-authors include Jing Qu, Guang‐Hui Liu, Weiqi Zhang, Moshi Song, Juan Carlos Izpisúa Belmonte, Zunpeng Liu, Shuai Ma, Piu Chan, Jie Ren and Zeming Wu. Their work appears in journals such as Protein & Cell, Nucleic Acids Research, Cell stem cell, Nature Aging and Advanced Materials Interfaces.
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.