Deepa Ghosh

1.4k citations
44 papers · 1.1k · h-index 17

Impact in

Papers in

    • Graphene and Nanomaterials Applications 6
    • Nanoplatforms for cancer theranostics 4
    • Bone Tissue Engineering Materials 4
    • Electrospun Nanofibers in Biomedical Applications 8

Deepa Ghosh

43 papers receiving 1.1k citations

Peers

Deepa Ghosh
Comparison fields: 5 of 109
  • Biomaterials 319
  • Molecular Medicine 106
  • Rehabilitation 140
  • Biomedical Engineering 438
  • Infectious Diseases 174
Replace Leila Mohammadi Amirabad with:
Leila Mohammadi Amirabad Iran
Yihao Liu China
Sina Sharifi United States
Lu Han China
Yuhang Jiang China
Nowsheen Goonoo Mauritius
Heidrun Steinle Germany
Yuan Yue China
Deepa Ghosh relative to Leila Mohammadi Amirabad Iran Leila Mohammadi Amirabad's profile →
Citations per field
00.5×2.9×
Leila Mohammadi Amirabad · 1×
Citations per year

Countries citing papers authored by Deepa Ghosh

Since Specialization
Citations

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

Fields of papers citing papers by Deepa Ghosh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Deepa Ghosh, 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 Deepa Ghosh Line = papers co-authored together Deepa Ghosh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020273
2 202293
3 201575
4 201472
5 201941
6 202039
7 202037
8 202135
9 202131
10 202227
11 202125
12 202023
13 201922
14 202122
15 201922
16 202420
17 202320
18 202416
19 202014
20 202214

About Deepa Ghosh

Deepa Ghosh is a scholar working on Biomedical Engineering, Biomaterials, Materials Chemistry, Molecular Biology and Rehabilitation, having authored 44 papers that have together received 1.1k indexed citations. Recurring topics across this work include Electrospun Nanofibers in Biomedical Applications (8 papers), Wound Healing and Treatments (7 papers), Graphene and Nanomaterials Applications (6 papers), Nanoplatforms for cancer theranostics (4 papers), Bone Tissue Engineering Materials (4 papers), Hydrogels: synthesis, properties, applications (4 papers), Osteoarthritis Treatment and Mechanisms (4 papers) and Tissue Engineering and Regenerative Medicine (3 papers). The work is most often cited by research in Biomaterials (319 citations), Molecular Medicine (106 citations), Rehabilitation (140 citations), Biomedical Engineering (438 citations) and Infectious Diseases (174 citations). Deepa Ghosh has collaborated with scholars based in India, United States and Mexico. Frequent co-authors include Vianni Chopra, Vineeta Panwar, Jijo Thomas, Anjana Sharma, Gaurav Chauhan, Sergio O. Martínez‐Chapa, Marc Madou, Sourav Kalra, Chandra Viswanathan and Swati Kaushik. Their work appears in journals such as ACS Biomaterials Science & Engineering, International Journal of Biological Macromolecules, Carbohydrate Polymers, ACS Applied Materials & Interfaces and ACS Applied Bio Materials.

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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