Deepak Parashar

1.5k total citations
53 papers, 859 citations indexed

About

Deepak Parashar is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Deepak Parashar has authored 53 papers receiving a total of 859 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 19 papers in Immunology and 17 papers in Oncology. Recurrent topics in Deepak Parashar's work include Immunotherapy and Immune Responses (10 papers), Extracellular vesicles in disease (8 papers) and MicroRNA in disease regulation (7 papers). Deepak Parashar is often cited by papers focused on Immunotherapy and Immune Responses (10 papers), Extracellular vesicles in disease (8 papers) and MicroRNA in disease regulation (7 papers). Deepak Parashar collaborates with scholars based in India, United States and France. Deepak Parashar's co-authors include Nirmala Jagadish, Anil Suri, Sumit Agarwal, Saurabh Gupta, Anjali Geethadevi, Nirmal Kumar Lohiya, Pradeep Chaluvally–Raghavan, Shikha Saini, Namita Gupta and Abdul S. Ansari and has published in prestigious journals such as SHILAP Revista de lepidopterología, Blood and PLoS ONE.

In The Last Decade

Deepak Parashar

52 papers receiving 846 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Deepak Parashar India 20 538 224 209 171 93 53 859
Kit Man Wong United States 13 368 0.7× 233 1.0× 151 0.7× 163 1.0× 99 1.1× 32 793
Jin Zhao China 18 576 1.1× 237 1.1× 255 1.2× 209 1.2× 121 1.3× 46 978
Chenliang Wang China 15 461 0.9× 332 1.5× 355 1.7× 179 1.0× 115 1.2× 28 947
Qiongfang Yu China 14 386 0.7× 143 0.6× 177 0.8× 130 0.8× 68 0.7× 31 662
Jinyong Wang China 17 550 1.0× 137 0.6× 104 0.5× 248 1.5× 69 0.7× 78 1.1k
Nick Huang United States 13 906 1.7× 287 1.3× 129 0.6× 246 1.4× 65 0.7× 16 1.3k
Н. В. Литвяков Russia 18 405 0.8× 417 1.9× 270 1.3× 154 0.9× 143 1.5× 110 955
Xing Gu China 17 621 1.2× 174 0.8× 203 1.0× 187 1.1× 62 0.7× 60 1.0k

Countries citing papers authored by Deepak Parashar

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Deepak Parashar

This figure shows the co-authorship network connecting the top 25 collaborators of Deepak Parashar. A scholar is included among the top collaborators of Deepak Parashar 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 Deepak Parashar. Deepak Parashar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Gupta, Saurabh, et al.. (2025). Extracellular vesicles in acute myeloid leukemia: The role in disease pathogenesis, potential biomarker, and application in clinical settings. Critical Reviews in Oncology/Hematology. 211. 104743–104743. 1 indexed citations
2.
Kashyap, Vivek K., et al.. (2025). KRAS Mutations in Cancer: Understanding Signaling Pathways to Immune Regulation and the Potential of Immunotherapy. Cancers. 17(5). 785–785. 3 indexed citations
3.
Parashar, Deepak, Rajan Pandey, Saurabh Gupta, et al.. (2025). Activated protein C promotes human lung cancer progression through the release of tumor extracellular vesicles and transfer of microRNA-200a. Cell Death and Disease. 16(1). 848–848.
4.
Gupta, Saurabh, et al.. (2024). Circulating Extracellular Vesicles: An Effective Biomarker for Cancer Progression. Frontiers in Bioscience-Landmark. 29(11). 375–375. 1 indexed citations
5.
Kumar, Akshay, et al.. (2024). Enhanced Music Recommendation Systems: A Comparative Study of Content-Based Filtering and K-Means Clustering Approaches. Revue d intelligence artificielle. 38(1). 365–376. 2 indexed citations
6.
Kaur, Rasanpreet, Saurabh Gupta, Vishal Khandelwal, et al.. (2024). Metabolomics-Driven Biomarker Discovery for Breast Cancer Prognosis and Diagnosis. Cells. 14(1). 5–5. 7 indexed citations
7.
Gupta, Saurabh, et al.. (2024). The role of extracellular vesicles in the pathogenesis of gynecological cancer. Frontiers in Oncology. 14. 2 indexed citations
8.
Parashar, Deepak, et al.. (2023). Transgenic Mouse Model for Translational Immunotherapy Studies on Multiple Myeloma. Blood. 142(Supplement 1). 6565–6565. 1 indexed citations
9.
Das, Kaushik, Subhojit Paul, Arnab Ghosh, et al.. (2023). Beyond Macromolecules: Extracellular Vesicles as Regulators of Inflammatory Diseases. Cells. 12(15). 1963–1963. 21 indexed citations
10.
Das, Kaushik, Subhojit Paul, Arnab Ghosh, et al.. (2023). Extracellular Vesicles in Triple–Negative Breast Cancer: Immune Regulation, Biomarkers, and Immunotherapeutic Potential. Cancers. 15(19). 4879–4879. 23 indexed citations
11.
Sun, Fumou, Yan Cheng, Deepak Parashar, et al.. (2023). IL6Myc mouse is an immunocompetent model for the development of aggressive multiple myeloma. Haematologica. 108(12). 3372–3383. 1 indexed citations
12.
Shankar, Prem, et al.. (2021). Genomic analysis of a novel species Halomonas shambharensis isolated from hypersaline lake in Northwest India. Molecular Biology Reports. 48(2). 1045–1053. 1 indexed citations
13.
14.
Parashar, Deepak, Anjali Geethadevi, Jasmine George, et al.. (2020). Peritoneal Spread of Ovarian Cancer Harbors Therapeutic Vulnerabilities Regulated by FOXM1 and EGFR/ERBB2 Signaling. Cancer Research. 80(24). 5554–5568. 29 indexed citations
15.
Geethadevi, Anjali, et al.. (2020). scFv6.C4 DNA vaccine with fragment C of tetanus toxin increases protective immunity against CEA-expressing tumor. Gene Therapy. 28(6). 287–289. 2 indexed citations
16.
Gong, Xianghui, Michael P. Endsley, Kevin R. Rarick, et al.. (2019). Interaction of tumor cells and astrocytes promotes breast cancer brain metastases through TGF-β2/ANGPTL4 axes. npj Precision Oncology. 3(1). 24–24. 65 indexed citations
17.
Bates, Amber M., Carol L. Fischer, Deepak Parashar, et al.. (2016). Predicting PD-L1 expression on human cancer cells using next-generation sequencing information in computational simulation models. Cancer Immunology Immunotherapy. 65(12). 1511–1522. 17 indexed citations
18.
Jagadish, Nirmala, Namita Gupta, Sumit Agarwal, et al.. (2016). Sperm-associated antigen 9 (SPAG9) promotes the survival and tumor growth of triple-negative breast cancer cells. Tumor Biology. 37(10). 13101–13110. 17 indexed citations
19.
Jagadish, Nirmala, Deepak Parashar, Namita Gupta, et al.. (2015). A-kinase anchor protein 4 (AKAP4) a promising therapeutic target of colorectal cancer. Journal of Experimental & Clinical Cancer Research. 34(1). 142–142. 33 indexed citations
20.
Saini, Shikha, Sumit Agarwal, Abhilasha Sinha, et al.. (2013). Gene silencing of A-kinase anchor protein 4 inhibits cervical cancer growth in vitro and in vivo. Cancer Gene Therapy. 20(7). 413–420. 20 indexed citations

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.

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