Prashant Dogra

48 papers receiving 962 citations

Peers

Prashant Dogra
Comparison fields: 5 of 107
  • Modeling and Simulation 204
  • Biomaterials 339
  • Pharmaceutical Science 74
  • Biomedical Engineering 317
  • Oncology 154
Replace Zhenzhong Zhang with:
Zhenzhong Zhang China
Seong H. Jang United States
Sara Nizzero United States
Srimeenakshi Srinivasan United States
Luisa M. Russell United States
Ron Kleiner Israel
Qinglin Shen China
Charlene M. Dawidczyk United States
Andrew S. Mikhail United States
Prashant Dogra relative to Zhenzhong Zhang China Zhenzhong Zhang's profile →
Citations per field
00.5×8.9×
Zhenzhong Zhang · 1×
Citations per year

Countries citing papers authored by Prashant Dogra

Since Specialization
Citations

This map shows the geographic impact of Prashant Dogra'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 Prashant Dogra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prashant Dogra more than expected).

Fields of papers citing papers by Prashant Dogra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Prashant Dogra. 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 Prashant Dogra. The network helps show where Prashant Dogra may publish in the future.

Co-authors

The 25 scholars most cited alongside Prashant Dogra, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Prashant Dogra Line = papers co-authored together Prashant Dogra links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018219
2 2019120
3 202077
4 202063
5 201649
6 201939
7 202235
8 202030
9 201430
10 202128
11 202123
12 202021
13 202117
14 202416
15 202216
16 202313
17 202013
18 202211
19 202311
20 202011

About Prashant Dogra

Prashant Dogra is a scholar working on Modeling and Simulation, Biomaterials, Oncology, Molecular Biology and Biomedical Engineering, having authored 50 papers that have together received 967 indexed citations. Recurring topics across this work include Mathematical Biology Tumor Growth (18 papers), Nanoparticle-Based Drug Delivery (15 papers), Cancer Cells and Metastasis (6 papers), Immunotherapy and Immune Responses (5 papers), Cancer Immunotherapy and Biomarkers (5 papers), COVID-19 epidemiological studies (4 papers), Field-Flow Fractionation Techniques (4 papers) and Advancements in Transdermal Drug Delivery (4 papers). The work is most often cited by research in Modeling and Simulation (204 citations), Biomaterials (339 citations), Pharmaceutical Science (74 citations), Biomedical Engineering (317 citations) and Oncology (154 citations). Prashant Dogra has collaborated with scholars based in United States, Italy and Switzerland. Frequent co-authors include Vittorio Cristini, Zhihui Wang, Joseph D. Butner, C. Jeffrey Brinker, Yao-Li Chuang, Achraf Noureddine, Javier Ruiz-Ramírez, Shreya Goel, Sergio Caserta and Kimberly S. Butler. Their work appears in journals such as International Journal of Pharmaceutics, Cancers, Science Advances, Wiley Interdisciplinary Reviews Nanomedicine and Nanobiotechnology and Scientific Reports.

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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