Arvind Thakkar

718 citations
22 papers · 549 · h-index 15

Impact in

Papers in

    • Genomics, phytochemicals, and oxidative stress 5
    • S100 Proteins and Annexins 2
    • RNA Interference and Gene Delivery 2
    • Sphingolipid Metabolism and Signaling 2
    • Drug Transport and Resistance Mechanisms 3

Arvind Thakkar

22 papers receiving 546 citations

Peers

Arvind Thakkar
Comparison fields: 5 of 78
  • Molecular Medicine 68
  • Biomaterials 125
  • Pharmaceutical Science 45
  • Toxicology 17
  • Cancer Research 70
Replace Mehdi Sabzichi with:
Mehdi Sabzichi Iran
Fardin Hashemi Türkiye
Foram U. Vaidya India
Ebrahim Rahmani Moghadam Iran
Ji Hyun Kim South Korea
Abir K. Panda India
Christos Kazazis Greece
Rishi K. Gara India
Yang Ke China
Madesh Belakavadi United States
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Citations per field
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Citations per year

Countries citing papers authored by Arvind Thakkar

Since Specialization
Citations

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

Fields of papers citing papers by Arvind Thakkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Arvind Thakkar, 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 Arvind Thakkar Line = papers co-authored together Arvind Thakkar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201771
2 201558
3 201256
4 201441
5 201035
6 201635
7 201333
8 201329
9 201928
10 201525
11 201525
12 201423
13
Novel nano-drug combination therapeutic regimen demonstrates significant efficacy in the transgenic mouse model of pancreatic ductal adenocarcinoma.
201819
14 201617
15 201516
16 201113
17 20179
18 20136
19 20105
20 20152

About Arvind Thakkar

Arvind Thakkar is a scholar working on Molecular Biology, Oncology, Molecular Medicine, Cancer Research and Cellular and Molecular Neuroscience, having authored 22 papers that have together received 549 indexed citations. Recurring topics across this work include Curcumin's Biomedical Applications (6 papers), Genomics, phytochemicals, and oxidative stress (5 papers), Drug Transport and Resistance Mechanisms (3 papers), Neuropeptides and Animal Physiology (3 papers), S100 Proteins and Annexins (2 papers), RNA Interference and Gene Delivery (2 papers), Barrier Structure and Function Studies (2 papers) and Sphingolipid Metabolism and Signaling (2 papers). The work is most often cited by research in Molecular Medicine (68 citations), Biomaterials (125 citations), Pharmaceutical Science (45 citations), Toxicology (17 citations) and Cancer Research (70 citations). Arvind Thakkar has collaborated with scholars based in United States, India and Netherlands. Frequent co-authors include Sunil Prabhu, Jeffrey Wang, Dhruvitkumar S. Sutaria, Zhijun Wang, Muralidhara Padigaru, Girish V. Shah, Baoyue Ding, Ravishankar Ravishankar, Arun Balakrishnan and David K. Ann. Their work appears in journals such as Cancer Research, Cell & Bioscience, International Journal of Oncology, Oncology Reports and Cancer Prevention Research.

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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