Supriya G. Prasanth
- Molecular Biology top 1%
- Cancer Research top 0.5%
- Cell Biology top 5%
- Genetics top 10%
- Atomic and Molecular Physics, and Optics top 10%
- Co-authors
- Kannanganattu V. PrasanthSusan M. FreierZhen ShenVidisha TripathiC. Frank BennettBruce StillmanDavid L. SpectorAlok Sharma
- Topics
- Genomics and Chromatin Dynamics (25 papers)DNA Repair Mechanisms (22 papers)RNA Research and Splicing (15 papers)
- Partner nations
- United StatesIndiaChina
In The Last Decade
Supriya G. Prasanth
59 papers receiving 5.2k citations
Hit Papers
Peers
Comparison fields: 5 of 117
- Molecular Biology 4.5k
- Cancer Research 2.7k
- Cell Biology 410
- Genetics 286
- Atomic and Molecular Physics, and Optics 266
Countries citing papers authored by Supriya G. Prasanth
This map shows the geographic impact of Supriya G. Prasanth'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 Supriya G. Prasanth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Supriya G. Prasanth more than expected).
Fields of papers citing papers by Supriya G. Prasanth
This network shows the impact of papers produced by Supriya G. Prasanth. 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 Supriya G. Prasanth. The network helps show where Supriya G. Prasanth may publish in the future.
Co-authorship network of co-authors of Supriya G. Prasanth
This figure shows the co-authorship network connecting the top 25 collaborators of Supriya G. Prasanth. A scholar is included among the top collaborators of Supriya G. Prasanth based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Supriya G. Prasanth. Supriya G. Prasanth is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 16 | |
| 4 | 13 | |
| 5 | 8 | |
| 6 | 15 | |
| 7 | 118 | |
| 8 | 21 | |
| 9 | 1 | |
| 10 | 15 | |
| 11 | Long Noncoding RNA MALAT1 Controls Cell Cycle Progression by Regulating the Expression of Oncogenic Transcription Factor B-MYBbreakdown → | 605 |
| 12 | 9 | |
| 13 | The Nuclear-Retained Noncoding RNA MALAT1 Regulates Alternative Splicing by Modulating SR Splicing Factor Phosphorylationbreakdown → | 1749 |
| 14 | 98 | |
| 15 | 110 | |
| 16 | Regulating Gene Expression through RNA Nuclear Retentionbreakdown → | 569 |
| 17 | 1 | |
| 18 | Medicinal Significance of Nitroimidazoles - Some Recent Advances | 18 |
| 19 | 6 | |
| 20 | 3 |
About Supriya G. Prasanth
Supriya G. Prasanth is a scholar working on Cancer Research, Molecular Biology and Cell Biology, having authored 60 papers that have together received 5.3k indexed citations. Recurring topics across this work include Genomics and Chromatin Dynamics (25 papers), DNA Repair Mechanisms (22 papers) and RNA Research and Splicing (15 papers). The work is most often cited by research in Cancer Research (2.7k citations), Molecular Biology (4.5k citations) and Biophysics (181 citations). Supriya G. Prasanth has collaborated with scholars based in United States, India and China. Frequent co-authors include Kannanganattu V. Prasanth, Susan M. Freier, Zhen Shen, Vidisha Tripathi, C. Frank Bennett, Bruce Stillman, David L. Spector, Alok Sharma, Andrew T. Watt and Jonathan D. Ellis. Their work appears in journals such as Science, Cell and Proceedings of the National Academy of Sciences.
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.