Vikash K. Sinha

1.2k citations
12 papers · 945 · h-index 11

Impact in

  • Pharmacology top 0.5%
    • Pharmacogenetics and Drug Metabolism
    • Antibiotics Pharmacokinetics and Efficacy
    • Drug-Induced Hepatotoxicity and Protection
    • Drug Solubulity and Delivery Systems

Papers in

Vikash K. Sinha

12 papers receiving 905 citations

Peers

Vikash K. Sinha
Comparison fields: 5 of 81
  • Pharmacology 498
  • Pharmaceutical Science 98
  • Computational Theory and Mathematics 222
  • Oncology 313
  • Spectroscopy 171
Replace Sheila Annie Peters with:
Sheila Annie Peters Germany
Rhys D.O. Jones United Kingdom
Ragini Vuppugalla United States
Ken Grime United Kingdom
Philip Wastall United States
Takafumi Iwatsubo Japan
Hugues Dolgos Germany
Zoe Barter United Kingdom
Leonid M. Berezhkovskiy United States
Heidi J. Einolf United States
Vikash K. Sinha relative to Sheila Annie Peters Germany Sheila Annie Peters's profile →
Citations per field
00.5×1.7×
Sheila Annie Peters · 1×
Citations per year

Countries citing papers authored by Vikash K. Sinha

Since Specialization
Citations

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

Fields of papers citing papers by Vikash K. Sinha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vikash K. Sinha. 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 Vikash K. Sinha. The network helps show where Vikash K. Sinha may publish in the future.

Co-authors

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

All Works

12 of 12 papers shown
#Work
1 2007205
2 2011158
3 2011141
4 2011111
5 200780
6 201267
7 201153
8 201147
9 200839
10 201522
11 201117
12 20095

About Vikash K. Sinha

Vikash K. Sinha is a scholar working on Pharmacology, Computational Theory and Mathematics, Statistics and Probability, Oncology and Spectroscopy, having authored 12 papers that have together received 945 indexed citations. Recurring topics across this work include Pharmacogenetics and Drug Metabolism (7 papers), Computational Drug Discovery Methods (4 papers), Statistical Methods in Clinical Trials (4 papers), Analytical Chemistry and Chromatography (3 papers), Drug Transport and Resistance Mechanisms (3 papers), Cardiac electrophysiology and arrhythmias (1 paper), Renal function and acid-base balance (1 paper) and Receptor Mechanisms and Signaling (1 paper). The work is most often cited by research in Pharmacology (498 citations), Pharmaceutical Science (98 citations), Computational Theory and Mathematics (222 citations), Oncology (313 citations) and Spectroscopy (171 citations). Vikash K. Sinha has collaborated with scholars based in Belgium, United States and Switzerland. Frequent co-authors include Claire Mackie, Ron Gilissen, Stefan S. De Buck, Marjoleen Nijsen, Luca A. Fenu, Kimberly K. Adkison, Punit Marathe, Patrick Poulin, Handan He and James Yates. Their work appears in journals such as Journal of Pharmaceutical Sciences, Drug Metabolism and Disposition, Clinical Pharmacokinetics, Advances in Chronic Kidney Disease and Biopharmaceutics & Drug Disposition.

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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