Derik E. Haggard

1.1k citations
22 papers · 857 · h-index 14

Impact in

Papers in

Derik E. Haggard

21 papers receiving 842 citations

Peers

Derik E. Haggard
Comparison fields: 5 of 98
  • Health, Toxicology and Mutagenesis 452
  • Small Animals 110
  • Pollution 125
  • Cancer Research 98
  • Biophysics 42
Replace Fred Parham with:
Fred Parham United States
Jui‐Hua Hsieh United States
Ram Ramabhadran United States
Matt T. Martin United States
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Albane le Maire France
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Nikolai Leonidovitch Chepelev Canada
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Citations per field
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Citations per year

Countries citing papers authored by Derik E. Haggard

Since Specialization
Citations

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

Fields of papers citing papers by Derik E. Haggard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Derik E. Haggard, 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 Derik E. Haggard Line = papers co-authored together Derik E. Haggard 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 2015256
2 2021141
3 2016100
4 201974
5 201650
6 201747
7 202034
8 201827
9 201920
10 202419
11 202318
12 201917
13 202214
14 201614
15 202410
16 20197
17 20223
18 20243
19 20251
20 20251

About Derik E. Haggard

Derik E. Haggard is a scholar working on Health, Toxicology and Mutagenesis, Computational Theory and Mathematics, Small Animals, Biophysics and Cell Biology, having authored 22 papers that have together received 857 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (12 papers), Effects and risks of endocrine disrupting chemicals (7 papers), Animal testing and alternatives (6 papers), Environmental Toxicology and Ecotoxicology (5 papers), Zebrafish Biomedical Research Applications (3 papers), Molecular Biology Techniques and Applications (3 papers), Cell Image Analysis Techniques (3 papers) and Gene expression and cancer classification (2 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (452 citations), Small Animals (110 citations), Pollution (125 citations), Cancer Research (98 citations) and Biophysics (42 citations). Derik E. Haggard has collaborated with scholars based in United States, United Kingdom and Ireland. Frequent co-authors include Robert L. Tanguay, Pamela D. Noyes, Greg D. Gonnerman, Richard Judson, Joshua Harrill, Imran Hussain Shah, Russell S. Thomas, R. Woodrow Setzer, Logan J. Everett and Clinton M. Willis. Their work appears in journals such as Toxicological Sciences, Current Opinion in Toxicology, Chemical Research in Toxicology, Toxicology and Toxicology and Applied Pharmacology.

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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