Phillip J. Daborn

5.6k citations
44 papers · 4.3k indexed · 1 hit paper · h-index 31

Phillip J. Daborn

44 papers receiving 4.2k citations

Hit Papers

A Single P450 Allele Associated with Insecticide Resistan...6752002202620102018200400600

Peers

Phillip J. Daborn
Comparison fields: 5 of 94
  • Insect Science 2.6k
  • Molecular Biology 2.7k
  • Plant Science 1.3k
  • Aging 48
  • Genetics 703
Replace Philip Batterham with:
Philip Batterham Australia
Gōngyín Yè China
Denise Valle Brazil
Wei Dou China
José L. Soulages United States
Douglas C. Knipple United States
Estela L. Arrese United States
A.K. Charnley United Kingdom
Hajime Ishikawa Japan
Ioannis Eleftherianos United States
Phillip J. Daborn relative to Philip Batterham Australia Philip Batterham's profile →
Citations per field
00.5×1.5×
Philip Batterham · 1×
Citations per year

Countries citing papers authored by Phillip J. Daborn

Since Specialization
Citations

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

Fields of papers citing papers by Phillip J. Daborn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Phillip J. Daborn. 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 Phillip J. Daborn. The network helps show where Phillip J. Daborn may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 201425
2 201337
3 201253
4 201273
5 2011147
6 201111
7 2010180
8 201048
9 200752
10 200614
11 200661
12 2004111
13 200427
14 2004322
15 2003145
16 200343
17 2003195
18
A Single P450 Allele Associated with Insecticide Resistance in Drosophilabreakdown →
2002675
19 200258
20 2002113

About Phillip J. Daborn

Phillip J. Daborn is a scholar working on Insect Science, Molecular Biology and Cellular and Molecular Neuroscience, having authored 44 papers that have together received 4.3k indexed citations. Recurring topics across this work include Insect Resistance and Genetics (35 papers), Insect and Pesticide Research (19 papers), Entomopathogenic Microorganisms in Pest Control (11 papers), Insect symbiosis and bacterial influences (9 papers), Insect-Plant Interactions and Control (9 papers), Neurobiology and Insect Physiology Research (8 papers), Insect Pest Control Strategies (6 papers) and CRISPR and Genetic Engineering (5 papers). The work is most often cited by research in Insect Science (2.6k citations), Molecular Biology (2.7k citations) and Plant Science (1.3k citations). Phillip J. Daborn has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include Richard H. ffrench‐Constant, Philip Batterham, Gaëlle Le Goff, Nicholas R. Waterfield, Henry Chung, Michael Bogwitz, Trent Perry, Janet L. Yen, Christopher Lumb and Charles Robin. Their work appears in journals such as Insect Biochemistry and Molecular Biology, Proceedings of the National Academy of Sciences, Pest Management Science, PLoS ONE and G3 Genes Genomes Genetics.

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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