Arijit Chakravarty
Impact in
- Cell Biology top 2%
- Microtubule and mitosis dynamics
- Oncology top 10%
- Cancer-related Molecular Pathways
Papers in
-
- Genomics and Chromatin Dynamics 4
- vaccines and immunoinformatics approaches 4
- Cell Biology 16
- Microtubule and mitosis dynamics 16
- Co-authors
- Jeffrey Ecsedy (9 shared papers)Jonathan M. Carlson (6 shared papers)Kara M. Hoar (3 shared papers)Deborah R. Wysong (3 shared papers)Robert Gross (5 shared papers)Mark Manfredi (8 shared papers)Douglas Bowman (2 shared papers)Charles E. DeZiel (2 shared papers)
- Journals
- PLoS ONE (7 papers)Cancer Research (5 papers)Vaccines (3 papers)Molecular Cancer Therapeutics (3 papers)BMC Public Health (2 papers)
- Partner nations
- United StatesJapanAustralia
In The Last Decade
Arijit Chakravarty
47 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 111
- Cell Biology 504
- Oncology 363
- Modeling and Simulation 50
- Molecular Biology 629
- Neurology 82
Countries citing papers authored by Arijit Chakravarty
This map shows the geographic impact of Arijit Chakravarty'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 Arijit Chakravarty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arijit Chakravarty more than expected).
Fields of papers citing papers by Arijit Chakravarty
This network shows the impact of papers produced by Arijit Chakravarty. 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 Arijit Chakravarty. The network helps show where Arijit Chakravarty may publish in the future.
Co-authors
The 25 scholars most cited alongside Arijit Chakravarty, 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 52 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 246 | |
| 2 | 2007 | 163 | |
| 3 | 2014 | 100 | |
| 4 | 2007 | 88 | |
| 5 | 2010 | 74 | |
| 6 | 2009 | 54 | |
| 7 | 2021 | 49 | |
| 8 | 2014 | 48 | |
| 9 | 2007 | 43 | |
| 10 | 2004 | 38 | |
| 11 | 2014 | 27 | |
| 12 | 2006 | 21 | |
| 13 | 2013 | 19 | |
| 14 | 2006 | 18 | |
| 15 | 2007 | 18 | |
| 16 | 2019 | 17 | |
| 17 | 2013 | 16 | |
| 18 | 2014 | 16 | |
| 19 | 2023 | 14 | |
| 20 | 2021 | 13 |
About Arijit Chakravarty
Arijit Chakravarty is a scholar working on Molecular Biology, Cell Biology, Infectious Diseases, Modeling and Simulation and Oncology, having authored 52 papers that have together received 1.2k indexed citations. Recurring topics across this work include Microtubule and mitosis dynamics (16 papers), COVID-19 epidemiological studies (11 papers), SARS-CoV-2 and COVID-19 Research (10 papers), Infection Control and Ventilation (4 papers), Cancer Treatment and Pharmacology (4 papers), Cancer-related Molecular Pathways (4 papers), Genomics and Chromatin Dynamics (4 papers) and vaccines and immunoinformatics approaches (4 papers). The work is most often cited by research in Cell Biology (504 citations), Oncology (363 citations), Modeling and Simulation (50 citations), Molecular Biology (629 citations) and Neurology (82 citations). Arijit Chakravarty has collaborated with scholars based in United States, Japan and Australia. Frequent co-authors include Jeffrey Ecsedy, Jonathan M. Carlson, Kara M. Hoar, Deborah R. Wysong, Robert Gross, Mark Manfredi, Douglas Bowman, Charles E. DeZiel, Vaishali Shinde and Claudia Rabino. Their work appears in journals such as PLoS ONE, Cancer Research, Vaccines, Molecular Cancer Therapeutics and BMC Public Health.
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.