Vigneshwari Subramanian
- Molecular Biology
- Computational Theory and Mathematics top 2%
- Materials Chemistry
- Pharmacology
- Biophysics top 10%
- Co-authors
- Julio Sáez-RodríguezGerd WohlfahrtAli OskooeiMatteo ManicaPeteris PrūsisJannis BornMaría Rodríguez MartínezIsidro Cortés‐Ciriano
- Topics
- Computational Drug Discovery Methods (12 papers)Machine Learning in Materials Science (6 papers)Cell Image Analysis Techniques (3 papers)
- Journals
- Nucleic Acids ResearchSHILAP Revista de lepidopterologíaeLife
- Partner nations
- United KingdomSwedenFinland
In The Last Decade
Vigneshwari Subramanian
14 papers receiving 320 citations
Peers
Comparison fields: 5 of 67
- Molecular Biology 243
- Computational Theory and Mathematics 210
- Materials Chemistry 76
- Pharmacology 27
- Biophysics 26
Countries citing papers authored by Vigneshwari Subramanian
This map shows the geographic impact of Vigneshwari Subramanian'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 Vigneshwari Subramanian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vigneshwari Subramanian more than expected).
Fields of papers citing papers by Vigneshwari Subramanian
This network shows the impact of papers produced by Vigneshwari Subramanian. 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 Vigneshwari Subramanian. The network helps show where Vigneshwari Subramanian may publish in the future.
Co-authorship network of co-authors of Vigneshwari Subramanian
This figure shows the co-authorship network connecting the top 25 collaborators of Vigneshwari Subramanian. A scholar is included among the top collaborators of Vigneshwari Subramanian 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 Vigneshwari Subramanian. Vigneshwari Subramanian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 5 | |
| 4 | 14 | |
| 5 | 7 | |
| 6 | 2 | |
| 7 | 37 | |
| 8 | 12 | |
| 9 | 32 | |
| 10 | 91 | |
| 11 | 6 | |
| 12 | 9 | |
| 13 | 83 | |
| 14 | 23 | |
| 15 | 3 |
About Vigneshwari Subramanian
Vigneshwari Subramanian is a scholar working on Computational Theory and Mathematics, Biophysics and Spectroscopy, having authored 15 papers that have together received 328 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (12 papers), Machine Learning in Materials Science (6 papers) and Cell Image Analysis Techniques (3 papers). The work is most often cited by research in Computational Theory and Mathematics (210 citations), Biophysics (26 citations) and Molecular Biology (243 citations). Vigneshwari Subramanian has collaborated with scholars based in United Kingdom, Sweden and Finland. Frequent co-authors include Julio Sáez-Rodríguez, Gerd Wohlfahrt, Ali Oskooei, Matteo Manica, Peteris Prūsis, Jannis Born, María Rodríguez Martínez, Isidro Cortés‐Ciriano, Eelke B. Lenselink and Gerard J. P. van Westen. Their work appears in journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and eLife.
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.