Soon Sim Tan
Impact in
- Cancer Research top 1%
- MicroRNA in disease regulation
- Genetics top 1%
- Mesenchymal stem cell research
Papers in
-
- Extracellular vesicles in disease 11
- RNA Interference and Gene Delivery 4
- Metabolism, Diabetes, and Cancer 1
-
- MicroRNA in disease regulation 7
- Co-authors
- Sai Kiang Lim (16 shared papers)Ruenn Chai Lai (8 shared papers)Yijun Yin (5 shared papers)Andre Choo (7 shared papers)Ronne Wee Yeh Yeo (6 shared papers)Bin Zhang (2 shared papers)Fatih Arslan (3 shared papers)Siu Kwan Sze (3 shared papers)
- Journals
- Journal of Extracellular Vesicles (3 papers)The Journal of Clinical Endocrinology & Metabolism (1 paper)Journal of Molecular and Cellular Cardiology (1 paper)Head & Neck (1 paper)Carcinogenesis (1 paper)
- Partner nations
- SingaporeNetherlandsBrazil
In The Last Decade
Soon Sim Tan
16 papers receiving 2.7k citations
Soon Sim Tan's Hit Papers
Peers
Comparison fields: 5 of 87
- Cancer Research 1.3k
- Genetics 650
- Molecular Biology 2.2k
- Immunology and Allergy 66
- Urology 66
Countries citing papers authored by Soon Sim Tan
This map shows the geographic impact of Soon Sim Tan'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 Soon Sim Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Soon Sim Tan more than expected).
Fields of papers citing papers by Soon Sim Tan
This network shows the impact of papers produced by Soon Sim Tan. 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 Soon Sim Tan. The network helps show where Soon Sim Tan may publish in the future.
Co-authors
The 25 scholars most cited alongside Soon Sim Tan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Mesenchymal stem cell: An efficient mass producer of exosomes for drug delivery Hit paper breakdown → | 2012 | 724 |
| 2 | Mesenchymal Stem Cells Secrete Immunologically Active Exosomes Hit paper breakdown → | 2013 | 576 |
| 3 | 2012 | 411 | |
| 4 | 2011 | 341 | |
| 5 | 2016 | 216 | |
| 6 | 2013 | 160 | |
| 7 | 2010 | 129 | |
| 8 | 2014 | 67 | |
| 9 | 2012 | 53 | |
| 10 | 2017 | 28 | |
| 11 | 2019 | 26 | |
| 12 | 2019 | 18 | |
| 13 | 2015 | 6 | |
| 14 | 2019 | 5 | |
| 15 | 2010 | 3 | |
| 16 | 2010 | 2 |
About Soon Sim Tan
Soon Sim Tan is a scholar working on Molecular Biology, Cancer Research, Genetics, Surgery and Obstetrics and Gynecology, having authored 16 papers that have together received 2.8k indexed citations. Recurring topics across this work include Extracellular vesicles in disease (11 papers), MicroRNA in disease regulation (7 papers), Mesenchymal stem cell research (4 papers), RNA Interference and Gene Delivery (4 papers), Pancreatic function and diabetes (2 papers), Pregnancy and preeclampsia studies (2 papers), Cell Adhesion Molecules Research (1 paper) and Metabolism, Diabetes, and Cancer (1 paper). The work is most often cited by research in Cancer Research (1.3k citations), Genetics (650 citations), Molecular Biology (2.2k citations), Immunology and Allergy (66 citations) and Urology (66 citations). Soon Sim Tan has collaborated with scholars based in Singapore, Netherlands and Brazil. Frequent co-authors include Sai Kiang Lim, Ruenn Chai Lai, Yijun Yin, Andre Choo, Ronne Wee Yeh Yeo, Bin Zhang, Bin Zhang, Fatih Arslan, Siu Kwan Sze and Dominique PV de Kleijn. Their work appears in journals such as Journal of Extracellular Vesicles, The Journal of Clinical Endocrinology & Metabolism, Journal of Molecular and Cellular Cardiology, Head & Neck and Carcinogenesis.
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.