Deepika Calidas
Impact in
- Aging top 1%
- Genetics, Aging, and Longevity in Model Organisms
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- RNA Research and Splicing
- RNA modifications and cancer
- RNA and protein synthesis mechanisms
- CRISPR and Genetic Engineering
- Nuclear Structure and Function
- Genomics and Chromatin Dynamics
Papers in
-
- RNA Research and Splicing 4
- RNA modifications and cancer 3
- RNA and protein synthesis mechanisms 2
- Fungal and yeast genetics research 1
- Nuclear Structure and Function 1
- Aging 4
- Genetics, Aging, and Longevity in Model Organisms 4
- Co-authors
- Jarrett Smith (4 shared papers)Helen Schmidt (4 shared papers)Géraldine Seydoux (4 shared papers)Dominique Rasoloson (3 shared papers)Alexandre Paix (2 shared papers)Tu Lu (2 shared papers)Jennifer T. Wang (1 shared paper)Bi‐Chang Chen (1 shared paper)
- Partner nations
- United StatesTaiwanUnited Kingdom
In The Last Decade
Deepika Calidas
6 papers receiving 718 citations
Deepika Calidas's Hit Papers
Peers
Comparison fields: 5 of 60
- Aging 227
- Molecular Biology 658
- Biochemistry 49
- Business and International Management 13
- Cell Biology 77
Countries citing papers authored by Deepika Calidas
This map shows the geographic impact of Deepika Calidas'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 Deepika Calidas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deepika Calidas more than expected).
Fields of papers citing papers by Deepika Calidas
This network shows the impact of papers produced by Deepika Calidas. 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 Deepika Calidas. The network helps show where Deepika Calidas may publish in the future.
Co-authors
The 15 scholars most cited alongside Deepika Calidas, 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 | Regulation of RNA granule dynamics by phosphorylation of serine-rich, intrinsically disordered proteins in C. elegans Hit paper breakdown → | 2014 | 304 |
| 2 | 2014 | 223 | |
| 3 | 2016 | 176 | |
| 4 | 2014 | 18 | |
| 5 | 2010 | 8 | |
| 6 | 2017 | 1 |
About Deepika Calidas
Deepika Calidas is a scholar working on Molecular Biology, Aging, Genetics, Infectious Diseases and Organic Chemistry, having authored 6 papers that have together received 730 indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (4 papers), RNA Research and Splicing (4 papers), RNA modifications and cancer (3 papers), RNA and protein synthesis mechanisms (2 papers), Evolution and Genetic Dynamics (1 paper), Fungal and yeast genetics research (1 paper), Bacterial Genetics and Biotechnology (1 paper) and Nuclear Structure and Function (1 paper). The work is most often cited by research in Aging (227 citations), Molecular Biology (658 citations), Biochemistry (49 citations), Business and International Management (13 citations) and Cell Biology (77 citations). Deepika Calidas has collaborated with scholars based in United States, Taiwan and United Kingdom. Frequent co-authors include Jarrett Smith, Helen Schmidt, Géraldine Seydoux, Dominique Rasoloson, Alexandre Paix, Tu Lu, Jennifer T. Wang, Bi‐Chang Chen, Eric Betzig and Bramwell G. Lambrus. Their work appears in journals such as eLife, RNA, Genetics and The FASEB Journal.
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.