Arabinda Ghosh
- Molecular Biology top 10%
- Computational Theory and Mathematics top 2%
- Organic Chemistry top 10%
- Biomedical Engineering top 10%
- Plant Science top 10%
- Co-authors
- Nobendu MukerjeeArun GoyalErmias Mergia TerefeDebabrat BaishyaAbhijit DeyMimosa GhoraiSwastika MaitraShradha Lakhera
- Topics
- Computational Drug Discovery Methods (31 papers)Enzyme Production and Characterization (10 papers)SARS-CoV-2 and COVID-19 Research (8 papers)
- Journals
- SHILAP Revista de lepidopterologíaThe Journal of Cell BiologyPLoS ONE
- Partner nations
- IndiaSaudi ArabiaUnited States
In The Last Decade
Arabinda Ghosh
103 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 143
- Molecular Biology 724
- Computational Theory and Mathematics 330
- Organic Chemistry 265
- Biomedical Engineering 263
- Plant Science 212
Countries citing papers authored by Arabinda Ghosh
This map shows the geographic impact of Arabinda Ghosh'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 Arabinda Ghosh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arabinda Ghosh more than expected).
Fields of papers citing papers by Arabinda Ghosh
This network shows the impact of papers produced by Arabinda Ghosh. 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 Arabinda Ghosh. The network helps show where Arabinda Ghosh may publish in the future.
Co-authorship network of co-authors of Arabinda Ghosh
This figure shows the co-authorship network connecting the top 25 collaborators of Arabinda Ghosh. A scholar is included among the top collaborators of Arabinda Ghosh 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 Arabinda Ghosh. Arabinda Ghosh 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 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 4 | |
| 8 | 13 | |
| 9 | Exosome-Based Smart Drug Delivery Tool for Cancer Theranosticsbreakdown → | 147 |
| 10 | 4 | |
| 11 | 5 | |
| 12 | 2 | |
| 13 | 22 | |
| 14 | 9 | |
| 15 | 8 | |
| 16 | 7 | |
| 17 | 31 | |
| 18 | 13 | |
| 19 | COMPARATIVE MODELLING AND LIGAND BINDING SITE PREDICTION OF A FAMILY 43 GLYCOSIDE HYDROLASE FROM Clostridium thermocellum | 2 |
| 20 | 40 |
About Arabinda Ghosh
Arabinda Ghosh is a scholar working on Computational Theory and Mathematics, Biotechnology and Pharmacology, having authored 106 papers that have together received 1.9k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (31 papers), Enzyme Production and Characterization (10 papers) and SARS-CoV-2 and COVID-19 Research (8 papers). The work is most often cited by research in Complementary and alternative medicine (174 citations), Computational Theory and Mathematics (330 citations) and Biotechnology (175 citations). Arabinda Ghosh has collaborated with scholars based in India, Saudi Arabia and United States. Frequent co-authors include Nobendu Mukerjee, Arun Goyal, Ermias Mergia Terefe, Debabrat Baishya, Abhijit Dey, Mimosa Ghorai, Swastika Maitra, Shradha Lakhera, Radha CHAUHAN and Meenakshi Rana. Their work appears in journals such as SHILAP Revista de lepidopterología, The Journal of Cell Biology and PLoS ONE.
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.