Jaykrishna Singh
Impact in
- Biomaterials top 5%
- Nanoparticle-Based Drug Delivery
-
- Nanoplatforms for cancer theranostics
- Characterization and Applications of Magnetic Nanoparticles
- Graphene and Nanomaterials Applications
- Microfluidic and Bio-sensing Technologies
Papers in
- Surgery 3
- Peripheral Artery Disease Management 3
- Coronary Interventions and Diagnostics 2
-
- Microtubule and mitosis dynamics 2
- Co-authors
- Paolo Decuzzi (7 shared papers)Santosh Aryal (2 shared papers)Cinzia Stigliano (2 shared papers)Anna Lisa Palange (2 shared papers)Daniele Di Mascolo (2 shared papers)Jaehong Key (1 shared paper)Enrica De Rosa (1 shared paper)Francesco Gentile (1 shared paper)
- Journals
- ACS Nano (2 papers)Journal of Biomechanics (1 paper)Computer Methods in Biomechanics & Biomedical Engineering (1 paper)BMC Systems Biology (1 paper)Advanced Healthcare Materials (1 paper)
- Partner nations
- United StatesItalySouth Korea
In The Last Decade
Jaykrishna Singh
11 papers receiving 513 citations
Peers
Comparison fields: 5 of 81
- Biomaterials 242
- Biomedical Engineering 245
- Molecular Medicine 27
- Modeling and Simulation 17
- Pharmaceutical Science 20
Countries citing papers authored by Jaykrishna Singh
This map shows the geographic impact of Jaykrishna Singh'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 Jaykrishna Singh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jaykrishna Singh more than expected).
Fields of papers citing papers by Jaykrishna Singh
This network shows the impact of papers produced by Jaykrishna Singh. 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 Jaykrishna Singh. The network helps show where Jaykrishna Singh may publish in the future.
Co-authors
The 25 scholars most cited alongside Jaykrishna Singh, 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 | 2014 | 181 | |
| 2 | 2015 | 154 | |
| 3 | 2017 | 36 | |
| 4 | 2009 | 33 | |
| 5 | 2012 | 25 | |
| 6 | 2015 | 25 | |
| 7 | 2013 | 22 | |
| 8 | 2013 | 12 | |
| 9 | 2016 | 10 | |
| 10 | 2019 | 9 | |
| 11 | 2012 | 7 |
About Jaykrishna Singh
Jaykrishna Singh is a scholar working on Surgery, Cell Biology, Modeling and Simulation, Biomedical Engineering and Pulmonary and Respiratory Medicine, having authored 11 papers that have together received 514 indexed citations. Recurring topics across this work include Mathematical Biology Tumor Growth (3 papers), Peripheral Artery Disease Management (3 papers), Coronary Interventions and Diagnostics (2 papers), Cancer Cells and Metastasis (2 papers), Nanoparticle-Based Drug Delivery (2 papers), Cerebrovascular and Carotid Artery Diseases (2 papers), Microtubule and mitosis dynamics (2 papers) and 3D Printing in Biomedical Research (1 paper). The work is most often cited by research in Biomaterials (242 citations), Biomedical Engineering (245 citations), Molecular Medicine (27 citations), Modeling and Simulation (17 citations) and Pharmaceutical Science (20 citations). Jaykrishna Singh has collaborated with scholars based in United States, Italy and South Korea. Frequent co-authors include Paolo Decuzzi, Santosh Aryal, Cinzia Stigliano, Anna Lisa Palange, Daniele Di Mascolo, Jaehong Key, Enrica De Rosa, Francesco Gentile, Yeonju Lee and Minjung Cho. Their work appears in journals such as ACS Nano, Journal of Biomechanics, Computer Methods in Biomechanics & Biomedical Engineering, BMC Systems Biology and Advanced Healthcare Materials.
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.