Priyanka De
- Computational Theory and Mathematics top 1%
- Molecular Biology
- Materials Chemistry
- Organic Chemistry
- Health, Toxicology and Mutagenesis top 10%
- Co-authors
- Kunal RoySupratik KarArkaprava BanerjeeMainak ChatterjeePravin AmbureHelena M. RamosVinay KumarAgnieszka Gajewicz
- Topics
- Computational Drug Discovery Methods (20 papers)Machine Learning in Materials Science (4 papers)Metabolomics and Mass Spectrometry Studies (3 papers)
- Journals
- The LancetSHILAP Revista de lepidopterologíaChemosphere
- Partner nations
- IndiaUnited StatesUnited Kingdom
In The Last Decade
Priyanka De
31 papers receiving 685 citations
Hit Papers
Peers
Comparison fields: 5 of 128
- Computational Theory and Mathematics 356
- Molecular Biology 153
- Materials Chemistry 92
- Organic Chemistry 88
- Health, Toxicology and Mutagenesis 70
Countries citing papers authored by Priyanka De
This map shows the geographic impact of Priyanka De'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 Priyanka De with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Priyanka De more than expected).
Fields of papers citing papers by Priyanka De
This network shows the impact of papers produced by Priyanka De. 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 Priyanka De. The network helps show where Priyanka De may publish in the future.
Co-authorship network of co-authors of Priyanka De
This figure shows the co-authorship network connecting the top 25 collaborators of Priyanka De. A scholar is included among the top collaborators of Priyanka De 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 Priyanka De. Priyanka De is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | Prediction reliability of QSAR models: an overview of various validation toolsbreakdown → | 115 |
| 3 | 27 | |
| 4 | 15 | |
| 5 | 11 | |
| 6 | 90 | |
| 7 | 5 | |
| 8 | 19 | |
| 9 | 18 | |
| 10 | The Pandemic and Economic Fallout in South Asia Challenges and the Way Forward | 3 |
| 11 | 10 | |
| 12 | 19 | |
| 13 | 21 | |
| 14 | 34 | |
| 15 | 1 | |
| 16 | 15 | |
| 17 | 46 | |
| 18 | 17 | |
| 19 | 15 | |
| 20 | CONTAINER PORT SYSTEM CONCENTRATION | 10 |
About Priyanka De
Priyanka De is a scholar working on Computational Theory and Mathematics, Analytical Chemistry and Environmental Chemistry, having authored 32 papers that have together received 705 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (20 papers), Machine Learning in Materials Science (4 papers) and Metabolomics and Mass Spectrometry Studies (3 papers). The work is most often cited by research in Computational Theory and Mathematics (356 citations), Analytical Chemistry (56 citations) and Health, Toxicology and Mutagenesis (70 citations). Priyanka De has collaborated with scholars based in India, United States and United Kingdom. Frequent co-authors include Kunal Roy, Supratik Kar, Arkaprava Banerjee, Mainak Chatterjee, Pravin Ambure, Helena M. Ramos, Vinay Kumar, Agnieszka Gajewicz, Arun Bandyopadhyay and Sreerupa Ghose Roy. Their work appears in journals such as The Lancet, SHILAP Revista de lepidopterología and Chemosphere.
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.