Vikram P. Sinha

83 papers receiving 2.6k citations

Peers

Vikram P. Sinha
Comparison fields: 5 of 134
  • Pharmacology 481
  • Statistics and Probability 249
  • Endocrinology, Diabetes and Metabolism 431
  • Oncology 578
  • Pediatrics, Perinatology and Child Health 338
Replace Jenny Y. Chien with:
Jenny Y. Chien United States
Dan M. Roden United States
Alexander Staab Germany
Ruth E. March United Kingdom
Rashmi R. Shah United Kingdom
Thomas Kerbusch Netherlands
Walter M. Cronin United States
QiPing Feng United States
Victoria M. Pratt United States
Vijay V. Upreti United States
Vikram P. Sinha relative to Jenny Y. Chien United States Jenny Y. Chien's profile →
Citations per field
00.5×2×2.6×
Jenny Y. Chien · 1×
Citations per year

Countries citing papers authored by Vikram P. Sinha

Since Specialization
Citations

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

Fields of papers citing papers by Vikram P. Sinha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015248
2 2018180
3 2006156
4 2005135
5 2020132
6 2014129
7 2009124
8 201299
9 200688
10 201288
11 201583
12 201375
13 201466
14 201661
15 201458
16 201352
17 200251
18 201451
19 201947
20 201445

About Vikram P. Sinha

Vikram P. Sinha is a scholar working on Statistics and Probability, Pharmacology, Pediatrics, Perinatology and Child Health, Endocrinology, Diabetes and Metabolism and Surgery, having authored 87 papers that have together received 2.7k indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (17 papers), Pharmaceutical studies and practices (16 papers), Diabetes Management and Research (13 papers), Pharmacogenetics and Drug Metabolism (12 papers), Diabetes Treatment and Management (12 papers), Pancreatic function and diabetes (6 papers), Health Systems, Economic Evaluations, Quality of Life (6 papers) and Computational Drug Discovery Methods (4 papers). The work is most often cited by research in Pharmacology (481 citations), Statistics and Probability (249 citations), Endocrinology, Diabetes and Metabolism (431 citations), Oncology (578 citations) and Pediatrics, Perinatology and Child Health (338 citations). Vikram P. Sinha has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Ping Zhao, Vicky Hsu, Christian Wagner, Joseph A. Grillo, Dinesh P. de Alwis, S-M Huang, Scott J. Jacober, Yuzhuo Pan, Daniel C. Howey and Yuanhang Pan. Their work appears in journals such as Clinical Pharmacology & Therapeutics, The Journal of Clinical Pharmacology, CPT Pharmacometrics & Systems Pharmacology, Diabetes Obesity and Metabolism and Diabetes Care.

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.

Explore authors with similar magnitude of impact