Parthasakha Das
- Modeling and Simulation top 1%
- Public Health, Environmental and Occupational Health top 10%
- Molecular Biology
- Genetics
- Statistical and Nonlinear Physics top 10%
- Co-authors
- Pritha DasRanjit Kumar UpadhyaySayan MukherjeeDibakar GhoshFathalla A. RihanA. K. MisraSanto BanerjeeSk Shahid Nadim
- Topics
- Mathematical and Theoretical Epidemiology and Ecology Models (15 papers)Mathematical Biology Tumor Growth (11 papers)Evolution and Genetic Dynamics (8 papers)
- Cited by
- Modeling and SimulationPublic Health, Environmental and Occupational HealthStatistical and Nonlinear Physics
- Journals
- Journal of Theoretical BiologyPhysica A Statistical Mechanics and its ApplicationsChaos Solitons & Fractals
- Partner nations
- IndiaUnited Arab EmiratesUnited States
In The Last Decade
Parthasakha Das
27 papers receiving 469 citations
Peers
Comparison fields: 5 of 82
- Modeling and Simulation 310
- Public Health, Environmental and Occupational Health 217
- Molecular Biology 104
- Genetics 91
- Statistical and Nonlinear Physics 65
Countries citing papers authored by Parthasakha Das
This map shows the geographic impact of Parthasakha Das'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 Parthasakha Das with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Parthasakha Das more than expected).
Fields of papers citing papers by Parthasakha Das
This network shows the impact of papers produced by Parthasakha Das. 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 Parthasakha Das. The network helps show where Parthasakha Das may publish in the future.
Co-authorship network of co-authors of Parthasakha Das
This figure shows the co-authorship network connecting the top 25 collaborators of Parthasakha Das. A scholar is included among the top collaborators of Parthasakha Das 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 Parthasakha Das. Parthasakha Das 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 | 1 | |
| 3 | 6 | |
| 4 | 6 | |
| 5 | 1 | |
| 6 | 7 | |
| 7 | 29 | |
| 8 | 24 | |
| 9 | 38 | |
| 10 | 1 | |
| 11 | 62 | |
| 12 | 30 | |
| 13 | 8 | |
| 14 | 12 | |
| 15 | 38 | |
| 16 | 37 | |
| 17 | 21 | |
| 18 | 34 | |
| 19 | 27 | |
| 20 | 18 |
About Parthasakha Das
Parthasakha Das is a scholar working on Modeling and Simulation, Public Health, Environmental and Occupational Health and Virology, having authored 28 papers that have together received 477 indexed citations. Recurring topics across this work include Mathematical and Theoretical Epidemiology and Ecology Models (15 papers), Mathematical Biology Tumor Growth (11 papers) and Evolution and Genetic Dynamics (8 papers). The work is most often cited by research in Modeling and Simulation (310 citations), Public Health, Environmental and Occupational Health (217 citations) and Statistical and Nonlinear Physics (65 citations). Parthasakha Das has collaborated with scholars based in India, United Arab Emirates and United States. Frequent co-authors include Pritha Das, Ranjit Kumar Upadhyay, Sayan Mukherjee, Dibakar Ghosh, Fathalla A. Rihan, A. K. Misra, Santo Banerjee, Sk Shahid Nadim, Muhammet Uzuntarla and Amitava Kundu. Their work appears in journals such as Journal of Theoretical Biology, Physica A Statistical Mechanics and its Applications and Chaos Solitons & Fractals.
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.