Vaskar Das

690 citations
24 papers · 535 · h-index 14

Impact in

  • Pharmacology top 10%
    • Musculoskeletal pain and rehabilitation
    • Inflammatory mediators and NSAID effects
    • Pain Mechanisms and Treatments

Papers in

Vaskar Das

23 papers receiving 526 citations

Peers

Vaskar Das
Comparison fields: 5 of 99
  • Pharmacology 168
  • Physiology 168
  • Anesthesiology and Pain Medicine 28
  • Biological Psychiatry 12
  • Pathology and Forensic Medicine 81
Replace Uroš Pecikoza with:
Uroš Pecikoza Serbia
Ana Micov Serbia
Ramin Ataee Iran
K. Steiner United States
Xin Fang China
Yan‐qiang Liu China
Hui Rong China
Amar S. More India
Juan Rodríguez‐Silverio Mexico
Vaskar Das relative to Uroš Pecikoza Serbia Uroš Pecikoza's profile →
Citations per field
00.5×3.9×
Uroš Pecikoza · 1×
Citations per year

Countries citing papers authored by Vaskar Das

Since Specialization
Citations

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

Fields of papers citing papers by Vaskar Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202178
2 198761
3 201652
4 201744
5 201735
6 201834
7 201934
8 201522
9 201921
10 201921
11 201818
12 201717
13 201916
14 201815
15 202213
16 201712
17 201912
18 201911
19 20169
20
Anti-diabetic Effect of Friedelan Triterpenoids in Streptozotocin Induced Diabetic Rat.
20153

About Vaskar Das

Vaskar Das is a scholar working on Physiology, Pharmacology, Molecular Biology, Pathology and Forensic Medicine and Endocrinology, Diabetes and Metabolism, having authored 24 papers that have together received 535 indexed citations. Recurring topics across this work include Pain Mechanisms and Treatments (16 papers), Musculoskeletal pain and rehabilitation (6 papers), Spine and Intervertebral Disc Pathology (5 papers), Natural Antidiabetic Agents Studies (3 papers), Phytochemicals and Antioxidant Activities (3 papers), Osteoarthritis Treatment and Mechanisms (2 papers), Botulinum Toxin and Related Neurological Disorders (2 papers) and Pharmacological Receptor Mechanisms and Effects (2 papers). The work is most often cited by research in Pharmacology (168 citations), Physiology (168 citations), Anesthesiology and Pain Medicine (28 citations), Biological Psychiatry (12 citations) and Pathology and Forensic Medicine (81 citations). Vaskar Das has collaborated with scholars based in United States, India and Canada. Frequent co-authors include Jeffrey S. Kroin, Mario Moric, Asokumar Buvanendran, Theodore J. Price, Gregory Dussor, Shilpi Ghosh, Wei Chen, Thomas C. W. Mak, Seik Weng Ng and André J. van Wijnen. Their work appears in journals such as Regional Anesthesia & Pain Medicine, Anesthesia & Analgesia, Gene, Journal of Cellular Physiology 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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