Alin Rai
Impact in
- Cancer Research top 1%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Molecular Biology top 2%
- Extracellular vesicles in disease
- Circular RNAs in diseases
- RNA Interference and Gene Delivery
Papers in
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- Extracellular vesicles in disease 35
- RNA Interference and Gene Delivery 6
- RNA Research and Splicing 5
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- MicroRNA in disease regulation 13
- Cancer-related molecular mechanisms research 6
- Co-authors
- David W. Greening (43 shared papers)Richard J. Simpson (21 shared papers)Rong Xu (16 shared papers)Maoshan Chen (14 shared papers)Wittaya Suwakulsiri (9 shared papers)Hong Ji (7 shared papers)Bethany Claridge (8 shared papers)Haoyun Fang (11 shared papers)
In The Last Decade
Alin Rai
42 papers receiving 3.1k citations
Alin Rai's Hit Papers
Peers
Comparison fields: 5 of 107
- Cancer Research 1.5k
- Molecular Biology 2.7k
- Immunology and Allergy 225
- Immunology 548
- Obstetrics and Gynecology 192
Countries citing papers authored by Alin Rai
This map shows the geographic impact of Alin Rai'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 Alin Rai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alin Rai more than expected).
Fields of papers citing papers by Alin Rai
This network shows the impact of papers produced by Alin Rai. 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 Alin Rai. The network helps show where Alin Rai may publish in the future.
Co-authors
The 25 scholars most cited alongside Alin Rai, 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 | Extracellular vesicles in cancer — implications for future improvements in cancer care Hit paper breakdown → | 2018 | 1144 |
| 2 | 2013 | 291 | |
| 3 | 2015 | 221 | |
| 4 | 2014 | 169 | |
| 5 | 2016 | 131 | |
| 6 | 2018 | 117 | |
| 7 | 2021 | 98 | |
| 8 | 2016 | 75 | |
| 9 | 2016 | 74 | |
| 10 | 2019 | 73 | |
| 11 | 2019 | 70 | |
| 12 | 2021 | 62 | |
| 13 | 2015 | 61 | |
| 14 | 2021 | 60 | |
| 15 | 2021 | 52 | |
| 16 | 2024 | 46 | |
| 17 | 2019 | 43 | |
| 18 | 2021 | 38 | |
| 19 | 2021 | 30 | |
| 20 | 2018 | 26 |
About Alin Rai
Alin Rai is a scholar working on Molecular Biology, Cancer Research, Immunology, Obstetrics and Gynecology and Oncology, having authored 43 papers that have together received 3.1k indexed citations. Recurring topics across this work include Extracellular vesicles in disease (35 papers), MicroRNA in disease regulation (13 papers), Reproductive System and Pregnancy (8 papers), Cancer-related molecular mechanisms research (6 papers), Pregnancy and preeclampsia studies (6 papers), RNA Interference and Gene Delivery (6 papers), RNA Research and Splicing (5 papers) and Cell Adhesion Molecules Research (4 papers). The work is most often cited by research in Cancer Research (1.5k citations), Molecular Biology (2.7k citations), Immunology and Allergy (225 citations), Immunology (548 citations) and Obstetrics and Gynecology (192 citations). Alin Rai has collaborated with scholars based in Australia, China and Japan. Frequent co-authors include David W. Greening, Richard J. Simpson, Rong Xu, Maoshan Chen, Wittaya Suwakulsiri, Hong Ji, Bethany Claridge, Haoyun Fang, Shashi K. Gopal and Qi Hui Poh. Their work appears in journals such as PROTEOMICS, Nature Reviews Clinical Oncology, Communications Biology, PLoS ONE and Molecular Human Reproduction.
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.