Gregg E. Dinse

2.4k citations
62 papers · 1.6k · h-index 23

Impact in

    • Statistical Methods and Inference
    • Statistical Methods and Bayesian Inference
    • Statistical Methods in Clinical Trials
    • Statistical Distribution Estimation and Applications

Papers in

    • Statistical Methods and Bayesian Inference 16
    • Statistical Methods and Inference 12
    • Statistical Distribution Estimation and Applications 6
    • Statistical Methods in Clinical Trials 6
    • Carcinogens and Genotoxicity Assessment 10

Gregg E. Dinse

56 papers receiving 1.5k citations

Peers

Gregg E. Dinse
Comparison fields: 5 of 145
  • Statistics and Probability 583
  • Health Informatics 30
  • Cancer Research 210
  • Health, Toxicology and Mutagenesis 208
  • Statistics, Probability and Uncertainty 83
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Amit Roy United States
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Citations per field
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Citations per year

Countries citing papers authored by Gregg E. Dinse

Since Specialization
Citations

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

Fields of papers citing papers by Gregg E. Dinse

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gregg E. Dinse. 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 Gregg E. Dinse. The network helps show where Gregg E. Dinse may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1982175
2 1985154
3 2000137
4 198296
5 198377
6 198657
7 201254
8 201051
9 198643
10 201443
11 201242
12 200241
13 200537
14 199535
15 198634
16 199426
17 198726
18 200725
19 199924
20 201124

About Gregg E. Dinse

Gregg E. Dinse is a scholar working on Statistics and Probability, Cancer Research, Health, Toxicology and Mutagenesis, Genetics and Small Animals, having authored 62 papers that have together received 1.6k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (16 papers), Statistical Methods and Inference (12 papers), Carcinogens and Genotoxicity Assessment (10 papers), Genetic and phenotypic traits in livestock (7 papers), Statistical Distribution Estimation and Applications (6 papers), Statistical Methods in Clinical Trials (6 papers), Effects and risks of endocrine disrupting chemicals (5 papers) and Toxic Organic Pollutants Impact (5 papers). The work is most often cited by research in Statistics and Probability (583 citations), Health Informatics (30 citations), Cancer Research (210 citations), Health, Toxicology and Mutagenesis (208 citations) and Statistics, Probability and Uncertainty (83 citations). Gregg E. Dinse has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Martin G. Larson, Stephen W. Lagakos, David B. Resnik, Shyamal D. Peddada, David B. Dunson, David M. Umbach, Bradley J. Collins, Moiz Mumtaz, Douglas Β. Tully and Cynthia S. Smith. Their work appears in journals such as Journal of the Royal Statistical Society Series C (Applied Statistics), Journal of the American Statistical Association, Biometrics, Frontiers in Immunology and Toxicologic Pathology.

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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