Nirav Shah
Impact in
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- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Pharmaceutical Science top 10%
Papers in
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- Circular RNAs in diseases 4
- Angiogenesis and VEGF in Cancer 2
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- MicroRNA in disease regulation 5
- Cancer-related molecular mechanisms research 4
- Co-authors
- Vivek P. Chavda (5 shared papers)Andrea M. Murphy (2 shared papers)Eric Hastie (2 shared papers)Pinku Mukherjee (2 shared papers)Valery Z. Grdzelishvili (2 shared papers)Megan Moerdyk‐Schauwecker (2 shared papers)Nam Y. Lee (5 shared papers)Yogin Patel (4 shared papers)
- Journals
- Frontiers in Pharmacology (2 papers)Nature Communications (1 paper)Molecular Cell (1 paper)The FASEB Journal (1 paper)Journal of Drug Delivery Science and Technology (1 paper)
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Nirav Shah
22 papers receiving 582 citations
Peers
Comparison fields: 5 of 89
- Cancer Research 127
- Pharmaceutical Science 32
- Rehabilitation 31
- Genetics 114
- Infectious Diseases 72
Countries citing papers authored by Nirav Shah
This map shows the geographic impact of Nirav Shah'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 Nirav Shah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nirav Shah more than expected).
Fields of papers citing papers by Nirav Shah
This network shows the impact of papers produced by Nirav Shah. 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 Nirav Shah. The network helps show where Nirav Shah may publish in the future.
Co-authors
The 25 scholars most cited alongside Nirav Shah, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 97 | |
| 2 | 2014 | 60 | |
| 3 | 2016 | 54 | |
| 4 | 1995 | 53 | |
| 5 | 2018 | 47 | |
| 6 | 2016 | 46 | |
| 7 | 2021 | 39 | |
| 8 | 2022 | 33 | |
| 9 | 2022 | 33 | |
| 10 | 2021 | 32 | |
| 11 | 2013 | 24 | |
| 12 | 2015 | 21 | |
| 13 | 2014 | 17 | |
| 14 | 2018 | 17 | |
| 15 | 2023 | 11 | |
| 16 | 2022 | 5 | |
| 17 | 1993 | 3 | |
| 18 | 2015 | 2 | |
| 19 | 2016 | 2 | |
| 20 | 2022 | 1 |
About Nirav Shah
Nirav Shah is a scholar working on Molecular Biology, Cancer Research, Infectious Diseases, Cardiology and Cardiovascular Medicine and Oncology, having authored 22 papers that have together received 599 indexed citations. Recurring topics across this work include MicroRNA in disease regulation (5 papers), Circular RNAs in diseases (4 papers), Cancer-related molecular mechanisms research (4 papers), COVID-19 Clinical Research Studies (3 papers), Inhalation and Respiratory Drug Delivery (2 papers), Drug Solubulity and Delivery Systems (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers) and Angiogenesis and VEGF in Cancer (2 papers). The work is most often cited by research in Cancer Research (127 citations), Pharmaceutical Science (32 citations), Rehabilitation (31 citations), Genetics (114 citations) and Infectious Diseases (72 citations). Nirav Shah has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Vivek P. Chavda, Andrea M. Murphy, Eric Hastie, Pinku Mukherjee, Valery Z. Grdzelishvili, Megan Moerdyk‐Schauwecker, Nam Y. Lee, Yogin Patel, Christopher C. Pan and Sanjay Kumar. Their work appears in journals such as Frontiers in Pharmacology, Nature Communications, Molecular Cell, The FASEB Journal and Journal of Drug Delivery Science and Technology.
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.