Will Dampier

46 papers receiving 1.6k citations

Will Dampier's Hit Papers

GOATOOLS: A Python library for Gene Ontology analyses 2018 · 765 citations
7650+2+5Years since publication250500750

Peers

Will Dampier
Comparison fields: 5 of 124
  • Virology 313
  • Business and International Management 50
  • Molecular Biology 852
  • Immunology 214
  • Aging 16
Replace Miria Ricchetti with:
Miria Ricchetti France
Yan Chai China
Pu Gao China
Elizabeth Fleming United States
Jian Zhu United States
Oliver Pusch Austria
Na Tang China
Martha F. Kramer United States
Will Dampier relative to Miria Ricchetti France Miria Ricchetti's profile →
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Countries citing papers authored by Will Dampier

Since Specialization
Citations

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

Fields of papers citing papers by Will Dampier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1
GOATOOLS: A Python library for Gene Ontology analyses
Hit paper breakdown →
2018765
2 2017178
3 202155
4 201852
5 201047
6 201041
7 201630
8 201730
9 201629
10 201928
11 201827
12 202026
13 201924
14 201724
15 201722
16 201420
17 201420
18 201620
19 201419
20 201618

About Will Dampier

Will Dampier is a scholar working on Virology, Molecular Biology, Infectious Diseases, Epidemiology and Public Health, Environmental and Occupational Health, having authored 48 papers that have together received 1.7k indexed citations. Recurring topics across this work include HIV Research and Treatment (30 papers), CRISPR and Genetic Engineering (15 papers), Mosquito-borne diseases and control (7 papers), HIV/AIDS Research and Interventions (6 papers), Advanced biosensing and bioanalysis techniques (5 papers), HIV/AIDS drug development and treatment (4 papers), Innovation and Socioeconomic Development (3 papers) and Cytomegalovirus and herpesvirus research (3 papers). The work is most often cited by research in Virology (313 citations), Business and International Management (50 citations), Molecular Biology (852 citations), Immunology (214 citations) and Aging (16 citations). Will Dampier has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Brian Wigdahl, Michael R. Nonnemacher, Haibao Tang, Aurélien Naldi, Liangsheng Zhang, Fidel Ramírez, Jeffrey M. Yunes, Chris Mungall, Patrick Flick and Olga Botvinnik. Their work appears in journals such as PLoS ONE, Frontiers in Microbiology, Scientific Reports, Current HIV Research and Journal of NeuroVirology.

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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