Deepak Parashar
Impact in
- Cancer Research top 10%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Oncology top 10%
- Cancer Immunotherapy and Biomarkers
- Cancer Cells and Metastasis
Papers in
-
- Extracellular vesicles in disease 8
- Circular RNAs in diseases 4
- Oncology 20
- Cancer Cells and Metastasis 5
- Cancer Immunotherapy and Biomarkers 4
- CAR-T cell therapy research 4
- Co-authors
- Sumit Agarwal (11 shared papers)Nirmala Jagadish (11 shared papers)Anil Suri (11 shared papers)Saurabh Gupta (19 shared papers)Anjali Geethadevi (14 shared papers)Nirmal Kumar Lohiya (8 shared papers)Pradeep Chaluvally–Raghavan (8 shared papers)Shikha Saini (6 shared papers)
- Journals
- Molecular Biology Reports (4 papers)OncoImmunology (4 papers)npj Precision Oncology (3 papers)Cancers (3 papers)Blood (2 papers)
- Partner nations
- IndiaUnited StatesFrance
In The Last Decade
Deepak Parashar
59 papers receiving 957 citations
Peers
Comparison fields: 5 of 98
- Cancer Research 187
- Oncology 215
- Immunology 160
- Molecular Biology 517
- Aging 7
Countries citing papers authored by Deepak Parashar
This map shows the geographic impact of Deepak Parashar'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 Deepak Parashar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deepak Parashar more than expected).
Fields of papers citing papers by Deepak Parashar
This network shows the impact of papers produced by Deepak Parashar. 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 Deepak Parashar. The network helps show where Deepak Parashar may publish in the future.
Co-authors
The 25 scholars most cited alongside Deepak Parashar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 65 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 69 | |
| 2 | 2022 | 59 | |
| 3 | 2016 | 49 | |
| 4 | 2022 | 48 | |
| 5 | 2023 | 42 | |
| 6 | 2020 | 38 | |
| 7 | 2013 | 38 | |
| 8 | 2012 | 37 | |
| 9 | 2013 | 37 | |
| 10 | 2015 | 34 | |
| 11 | 2020 | 33 | |
| 12 | 2013 | 33 | |
| 13 | 2019 | 28 | |
| 14 | 2023 | 25 | |
| 15 | 2023 | 23 | |
| 16 | 2021 | 23 | |
| 17 | 2018 | 23 | |
| 18 | 2022 | 23 | |
| 19 | 2016 | 21 | |
| 20 | 2013 | 21 |
About Deepak Parashar
Deepak Parashar is a scholar working on Molecular Biology, Oncology, Immunology, Cancer Research and Hematology, having authored 65 papers that have together received 972 indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (8 papers), Extracellular vesicles in disease (8 papers), MicroRNA in disease regulation (7 papers), Cancer Cells and Metastasis (5 papers), Circular RNAs in diseases (4 papers), Cancer Immunotherapy and Biomarkers (4 papers), Immune Cell Function and Interaction (4 papers) and CAR-T cell therapy research (4 papers). The work is most often cited by research in Cancer Research (187 citations), Oncology (215 citations), Immunology (160 citations), Molecular Biology (517 citations) and Aging (7 citations). Deepak Parashar has collaborated with scholars based in India, United States and France. Frequent co-authors include Sumit Agarwal, Nirmala Jagadish, Anil Suri, Saurabh Gupta, Anjali Geethadevi, Nirmal Kumar Lohiya, Pradeep Chaluvally–Raghavan, Shikha Saini, Namita Gupta and Vivek K. Kashyap. Their work appears in journals such as Molecular Biology Reports, OncoImmunology, npj Precision Oncology, Cancers and Blood.
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.