Kannan Subbaram
- Infectious Diseases top 5%
- Molecular Biology
- Epidemiology
- Radiology, Nuclear Medicine and Imaging
- Modeling and Simulation top 5%
- Co-authors
- K. HemalathaP. Shaik Syed AliSheeza AliAhmed ZeynudinMansour K. GatashehDaniel YilmaNegussie BeyeneMajed M. Masadeh
- Topics
- SARS-CoV-2 and COVID-19 Research (8 papers)COVID-19 Clinical Research Studies (6 papers)Aquaculture disease management and microbiota (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaFitoterapiaMedical Hypotheses
In The Last Decade
Kannan Subbaram
37 papers receiving 943 citations
Peers
Comparison fields: 5 of 142
- Infectious Diseases 422
- Molecular Biology 191
- Epidemiology 100
- Radiology, Nuclear Medicine and Imaging 75
- Modeling and Simulation 71
Countries citing papers authored by Kannan Subbaram
This map shows the geographic impact of Kannan Subbaram'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 Kannan Subbaram with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kannan Subbaram more than expected).
Fields of papers citing papers by Kannan Subbaram
This network shows the impact of papers produced by Kannan Subbaram. 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 Kannan Subbaram. The network helps show where Kannan Subbaram may publish in the future.
Co-authorship network of co-authors of Kannan Subbaram
This figure shows the co-authorship network connecting the top 25 collaborators of Kannan Subbaram. A scholar is included among the top collaborators of Kannan Subbaram 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 Kannan Subbaram. Kannan Subbaram is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 3 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 0 | |
| 11 | 4 | |
| 12 | 23 | |
| 13 | 0 | |
| 14 | 11 | |
| 15 | Isolation and characterization of probiotic bacteria isolated from diverse fish fauna of the trodden Vaigai river at Theni district. | 2 |
| 16 | In-vitro antibacterial activity of various extract of Mirabilis Jalapa stem | 3 |
| 17 | 2 | |
| 18 | 8 | |
| 19 | 13 | |
| 20 | 8 |
About Kannan Subbaram
Kannan Subbaram is a scholar working on Physiology, Virology and Health Informatics, having authored 46 papers that have together received 989 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (8 papers), COVID-19 Clinical Research Studies (6 papers) and Aquaculture disease management and microbiota (4 papers). The work is most often cited by research in Infectious Diseases (422 citations), Applied Microbiology and Biotechnology (45 citations) and Modeling and Simulation (71 citations). Kannan Subbaram has collaborated with scholars based in Maldives, Ethiopia and India. Frequent co-authors include K. Hemalatha, P. Shaik Syed Ali, Sheeza Ali, Ahmed Zeynudin, Mansour K. Gatasheh, Daniel Yilma, Negussie Beyene, Majed M. Masadeh, Ranjit Sah and Amol D. Gholap. Their work appears in journals such as SHILAP Revista de lepidopterología, Fitoterapia and Medical Hypotheses.
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.