Deep Pandya
Impact in
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- Cancer Genomics and Diagnostics
- Cancer-related molecular mechanisms research
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- Pancreatic and Hepatic Oncology Research
- Cancer-related Molecular Pathways
- Viral-associated cancers and disorders
Papers in
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- Metabolism, Diabetes, and Cancer 2
- Circular RNAs in diseases 2
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- Cancer Genomics and Diagnostics 5
- Cancer-related molecular mechanisms research 4
- MicroRNA in disease regulation 2
- Co-authors
- Cristiano Ferlini (7 shared papers)Roshan Karki (2 shared papers)Robert C. Elston (1 shared paper)Marisa Mariani (6 shared papers)Paul Fiedler (6 shared papers)Giovanni Scambia (3 shared papers)Richard C. Frank (5 shared papers)Mara Fanelli (2 shared papers)
- Journals
- Molecular Case Studies (3 papers)PLoS ONE (3 papers)Pancreas (2 papers)Cancer Research (1 paper)Frontiers in Oncology (1 paper)
- Partner nations
- United StatesItalyChina
In The Last Decade
Deep Pandya
18 papers receiving 346 citations
Peers
Comparison fields: 5 of 91
- Cancer Research 71
- Oncology 105
- Reproductive Medicine 23
- Molecular Biology 174
- Cell Biology 38
Countries citing papers authored by Deep Pandya
This map shows the geographic impact of Deep Pandya'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 Deep Pandya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deep Pandya more than expected).
Fields of papers citing papers by Deep Pandya
This network shows the impact of papers produced by Deep Pandya. 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 Deep Pandya. The network helps show where Deep Pandya may publish in the future.
Co-authors
The 25 scholars most cited alongside Deep Pandya, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 138 | |
| 2 | 2015 | 64 | |
| 3 | 2015 | 28 | |
| 4 | Nek6 and Hif-1α cooperate with the cytoskeletal gateway of drug resistance to drive outcome in serous ovarian cancer. | 2015 | 24 |
| 5 | 2014 | 21 | |
| 6 | 2019 | 15 | |
| 7 | 2014 | 13 | |
| 8 | 2021 | 11 | |
| 9 | 2021 | 10 | |
| 10 | 2018 | 8 | |
| 11 | 2022 | 6 | |
| 12 | 2015 | 4 | |
| 13 | 2025 | 3 | |
| 14 | 2025 | 2 | |
| 15 | 2019 | 2 | |
| 16 | 2025 | 1 | |
| 17 | 2025 | 1 | |
| 18 | 2012 | 1 | |
| 19 | 2022 | 0 |
About Deep Pandya
Deep Pandya is a scholar working on Molecular Biology, Cancer Research, Oncology, Pulmonary and Respiratory Medicine and Cell Biology, having authored 19 papers that have together received 352 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (5 papers), Cancer-related molecular mechanisms research (4 papers), Pancreatic and Hepatic Oncology Research (4 papers), Metabolism, Diabetes, and Cancer (2 papers), Pancreatitis Pathology and Treatment (2 papers), MicroRNA in disease regulation (2 papers), PARP inhibition in cancer therapy (2 papers) and Circular RNAs in diseases (2 papers). The work is most often cited by research in Cancer Research (71 citations), Oncology (105 citations), Reproductive Medicine (23 citations), Molecular Biology (174 citations) and Cell Biology (38 citations). Deep Pandya has collaborated with scholars based in United States, Italy and China. Frequent co-authors include Cristiano Ferlini, Roshan Karki, Robert C. Elston, Marisa Mariani, Paul Fiedler, Giovanni Scambia, Richard C. Frank, Mara Fanelli, Marco Petrillo and Giuseppina Raspaglio. Their work appears in journals such as Molecular Case Studies, PLoS ONE, Pancreas, Cancer Research and Frontiers in Oncology.
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.