Manoj Gopalkrishnan
- Molecular Biology
- Statistical and Nonlinear Physics top 10%
- Biomedical Engineering
- Infectious Diseases
- Ecology
- Co-authors
- Yuriy BrunDustin ReishusAnne ShiuN. V. ChelyapovLeonard M. AdlemanEzra MillerCarsten WiufGheorghe Crăciun
- Topics
- Gene Regulatory Network Analysis (5 papers)Advanced biosensing and bioanalysis techniques (5 papers)DNA and Nucleic Acid Chemistry (4 papers)
- Journals
- Journal of the American Chemical SocietyJournal of The Royal Society InterfaceProceedings of the Royal Society A Mathematical Physical and Engineering Sciences
- Partner nations
- IndiaUnited StatesDenmark
In The Last Decade
Manoj Gopalkrishnan
15 papers receiving 258 citations
Peers
Comparison fields: 5 of 53
- Molecular Biology 180
- Statistical and Nonlinear Physics 54
- Biomedical Engineering 39
- Infectious Diseases 34
- Ecology 28
Countries citing papers authored by Manoj Gopalkrishnan
This map shows the geographic impact of Manoj Gopalkrishnan'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 Manoj Gopalkrishnan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manoj Gopalkrishnan more than expected).
Fields of papers citing papers by Manoj Gopalkrishnan
This network shows the impact of papers produced by Manoj Gopalkrishnan. 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 Manoj Gopalkrishnan. The network helps show where Manoj Gopalkrishnan may publish in the future.
Co-authorship network of co-authors of Manoj Gopalkrishnan
This figure shows the co-authorship network connecting the top 25 collaborators of Manoj Gopalkrishnan. A scholar is included among the top collaborators of Manoj Gopalkrishnan 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 Manoj Gopalkrishnan. Manoj Gopalkrishnan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 3 | |
| 3 | 26 | |
| 4 | A Compressed Sensing Approach to Group-testing for COVID-19 Detection | 8 |
| 5 | 8 | |
| 6 | 9 | |
| 7 | 3 | |
| 8 | 32 | |
| 9 | 12 | |
| 10 | 48 | |
| 11 | 4 | |
| 12 | 8 | |
| 13 | Toward in vivo disease diagnosis and treatment using DNA | 1 |
| 14 | Building blocks for DNA self-assembly | 7 |
| 15 | 91 |
About Manoj Gopalkrishnan
Manoj Gopalkrishnan is a scholar working on Modeling and Simulation, Statistical and Nonlinear Physics and Infectious Diseases, having authored 15 papers that have together received 264 indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (5 papers), Advanced biosensing and bioanalysis techniques (5 papers) and DNA and Nucleic Acid Chemistry (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (54 citations), Molecular Biology (180 citations) and Modeling and Simulation (10 citations). Manoj Gopalkrishnan has collaborated with scholars based in India, United States and Denmark. Frequent co-authors include Yuriy Brun, Dustin Reishus, Anne Shiu, N. V. Chelyapov, Leonard M. Adleman, Ezra Miller, Carsten Wiuf, Gheorghe Crăciun, David F. Anderson and Thomas E. Ouldridge. Their work appears in journals such as Journal of the American Chemical Society, Journal of The Royal Society Interface and Proceedings of the Royal Society A Mathematical Physical and Engineering 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.