Jayesh A. Kulkarni
- Molecular Biology top 1%
- Biomedical Engineering top 2%
- Biomaterials top 1%
- Immunology top 2%
- Infectious Diseases top 2%
- Co-authors
- Pieter R. CullisDominik WitzigmannRoy van der MeelSam ChenYuen Yi C. TamRein VerbekeWim JiskootLinde Schoenmaker
- Topics
- RNA Interference and Gene Delivery (33 papers)Advanced biosensing and bioanalysis techniques (19 papers)Lipid Membrane Structure and Behavior (15 papers)
- Journals
- Proceedings of the National Academy of SciencesAdvanced MaterialsAccounts of Chemical Research
- Partner nations
- CanadaNetherlandsUnited States
In The Last Decade
Jayesh A. Kulkarni
45 papers receiving 7.2k citations
Hit Papers
Peers
Comparison fields: 5 of 134
- Molecular Biology 5.8k
- Biomedical Engineering 1.1k
- Biomaterials 1.0k
- Immunology 995
- Infectious Diseases 797
Countries citing papers authored by Jayesh A. Kulkarni
This map shows the geographic impact of Jayesh A. Kulkarni'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 Jayesh A. Kulkarni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jayesh A. Kulkarni more than expected).
Fields of papers citing papers by Jayesh A. Kulkarni
This network shows the impact of papers produced by Jayesh A. Kulkarni. 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 Jayesh A. Kulkarni. The network helps show where Jayesh A. Kulkarni may publish in the future.
Co-authorship network of co-authors of Jayesh A. Kulkarni
This figure shows the co-authorship network connecting the top 25 collaborators of Jayesh A. Kulkarni. A scholar is included among the top collaborators of Jayesh A. Kulkarni 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 Jayesh A. Kulkarni. Jayesh A. Kulkarni is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 15 | |
| 6 | 12 | |
| 7 | Induction of Bleb Structures in Lipid Nanoparticle Formulations of mRNA Leads to Improved Transfection Potencybreakdown → | 129 |
| 8 | 27 | |
| 9 | 12 | |
| 10 | 42 | |
| 11 | 16 | |
| 12 | The current landscape of nucleic acid therapeuticsbreakdown → | 934 |
| 13 | 42 | |
| 14 | 49 | |
| 15 | 25 | |
| 16 | The Onpattro story and the clinical translation of nanomedicines containing nucleic acid-based drugsbreakdown → | 1160 |
| 17 | 29 | |
| 18 | 52 | |
| 19 | 74 | |
| 20 | 176 |
About Jayesh A. Kulkarni
Jayesh A. Kulkarni is a scholar working on Biomaterials, Pharmaceutical Science and Molecular Biology, having authored 47 papers that have together received 7.2k indexed citations. Recurring topics across this work include RNA Interference and Gene Delivery (33 papers), Advanced biosensing and bioanalysis techniques (19 papers) and Lipid Membrane Structure and Behavior (15 papers). The work is most often cited by research in Molecular Biology (5.8k citations), Biomaterials (1.0k citations) and Pharmaceutical Science (365 citations). Jayesh A. Kulkarni has collaborated with scholars based in Canada, Netherlands and United States. Frequent co-authors include Pieter R. Cullis, Dominik Witzigmann, Roy van der Meel, Sam Chen, Yuen Yi C. Tam, Rein Verbeke, Wim Jiskoot, Linde Schoenmaker, Gideon Kersten and Daan J.A. Crommelin. Their work appears in journals such as Proceedings of the National Academy of Sciences, Advanced Materials and Accounts of Chemical Research.
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.