J. Krishnan
Impact in
- Biophysics top 10%
- Advanced Fluorescence Microscopy Techniques
- Modeling and Simulation top 10%
Papers in
-
- Gene Regulatory Network Analysis 23
- RNA and protein synthesis mechanisms 7
- Protein Structure and Dynamics 6
- Cell Biology 13
- Cellular Mechanics and Interactions 9
- Microtubule and mitosis dynamics 5
- Co-authors
- Pablo A. Iglesias (6 shared papers)Daniel D. Seaton (4 shared papers)Yun‐Bo Zhao (2 shared papers)Xiao Yun Xu (4 shared papers)Justin Stebbing (1 shared paper)Ian Stansfield (1 shared paper)Andre Levchenko (1 shared paper)Cong Liu (1 shared paper)
- Journals
- Journal of Theoretical Biology (6 papers)Journal of The Royal Society Interface (5 papers)BMC Systems Biology (4 papers)Integrative Biology (3 papers)Biophysical Journal (3 papers)
- Partner nations
- United KingdomUnited StatesThailand
In The Last Decade
J. Krishnan
42 papers receiving 397 citations
Peers
Comparison fields: 5 of 79
- Biophysics 47
- Modeling and Simulation 23
- Cell Biology 81
- Molecular Biology 286
- Computational Theory and Mathematics 30
Countries citing papers authored by J. Krishnan
This map shows the geographic impact of J. Krishnan'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 J. Krishnan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Krishnan more than expected).
Fields of papers citing papers by J. Krishnan
This network shows the impact of papers produced by J. Krishnan. 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 J. Krishnan. The network helps show where J. Krishnan may publish in the future.
Co-authors
The 11 scholars most cited alongside J. Krishnan, 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 42 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2002 | 30 | |
| 2 | 2015 | 30 | |
| 3 | 2014 | 23 | |
| 4 | 2004 | 19 | |
| 5 | 2006 | 18 | |
| 6 | 2015 | 17 | |
| 7 | 2011 | 14 | |
| 8 | 2013 | 14 | |
| 9 | 2012 | 13 | |
| 10 | 2004 | 13 | |
| 11 | 2019 | 12 | |
| 12 | 2012 | 11 | |
| 13 | 2015 | 11 | |
| 14 | 2011 | 11 | |
| 15 | 2011 | 11 | |
| 16 | 2011 | 10 | |
| 17 | 2009 | 10 | |
| 18 | 2016 | 10 | |
| 19 | 2004 | 10 | |
| 20 | 2010 | 9 |
About J. Krishnan
J. Krishnan is a scholar working on Molecular Biology, Cell Biology, Biophysics, Genetics and Oncology, having authored 42 papers that have together received 401 indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (23 papers), Cellular Mechanics and Interactions (9 papers), Advanced Fluorescence Microscopy Techniques (7 papers), RNA and protein synthesis mechanisms (7 papers), Bacterial Genetics and Biotechnology (6 papers), Protein Structure and Dynamics (6 papers), Microtubule and mitosis dynamics (5 papers) and Cell Image Analysis Techniques (4 papers). The work is most often cited by research in Biophysics (47 citations), Modeling and Simulation (23 citations), Cell Biology (81 citations), Molecular Biology (286 citations) and Computational Theory and Mathematics (30 citations). J. Krishnan has collaborated with scholars based in United Kingdom, United States and Thailand. Frequent co-authors include Pablo A. Iglesias, Daniel D. Seaton, Yun‐Bo Zhao, Xiao Yun Xu, Justin Stebbing, Ian Stansfield, Andre Levchenko, Cong Liu, Sumit Paliwal and Eric de Silva. Their work appears in journals such as Journal of Theoretical Biology, Journal of The Royal Society Interface, BMC Systems Biology, Integrative Biology and Biophysical 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.