Ken Tan

2.4k citations
102 papers · 1.9k · h-index 24

Impact in

Papers in

    • Insect and Arachnid Ecology and Behavior 90
    • Insect and Pesticide Research 87
    • Bee Products Chemical Analysis 6

Ken Tan

99 papers receiving 1.9k citations

Peers

Ken Tan
Comparison fields: 5 of 115
  • Insect Science 1.5k
  • Ecology, Evolution, Behavior and Systematics 1.4k
  • Genetics 1.4k
  • Cellular and Molecular Neuroscience 97
  • Developmental Biology 8
Replace Margaret J. Couvillon with:
Margaret J. Couvillon United Kingdom
Didier Crauser France
Freddie‐Jeanne Richard France
Vincent Dietemann Switzerland
Per Kryger Denmark
Faith M. Oi United States
John H. Klotz United States
Alain Robert France
Gard W. Otis Canada
David F. Williams United States
Ken Tan relative to Margaret J. Couvillon United Kingdom Margaret J. Couvillon's profile →
Citations per field
00.5×1.6×
Margaret J. Couvillon · 1×
Citations per year

Countries citing papers authored by Ken Tan

Since Specialization
Citations

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

Fields of papers citing papers by Ken Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 102 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007108
2 2015106
3 2010105
4 201486
5 201286
6 201753
7 201249
8
Comparison of Medfly male-only and bisexual releases in large scale field trials.
200048
9 201647
10 201743
11 201342
12 200541
13 200737
14 201836
15 201634
16 201432
17 201629
18 201629
19 202327
20 201627

About Ken Tan

Ken Tan is a scholar working on Genetics, Insect Science, Ecology, Evolution, Behavior and Systematics, Cellular and Molecular Neuroscience and Pharmacology, having authored 102 papers that have together received 1.9k indexed citations. Recurring topics across this work include Insect and Arachnid Ecology and Behavior (90 papers), Insect and Pesticide Research (87 papers), Plant and animal studies (84 papers), Bee Products Chemical Analysis (6 papers), Neurobiology and Insect Physiology Research (3 papers), Antimicrobial Peptides and Activities (2 papers), Animal Behavior and Reproduction (2 papers) and Healthcare and Venom Research (2 papers). The work is most often cited by research in Insect Science (1.5k citations), Ecology, Evolution, Behavior and Systematics (1.4k citations), Genetics (1.4k citations), Cellular and Molecular Neuroscience (97 citations) and Developmental Biology (8 citations). Ken Tan has collaborated with scholars based in China, United States and South Africa. Frequent co-authors include James C. Nieh, Shihao Dong, Sarah E. Radloff, H. R. Hepburn, Benjamin P. Oldroyd, Zhengwei Wang, Xiwen Liu, Weiwen Chen, Zhengwei Wang and Ping Wen. Their work appears in journals such as Apidologie, Journal of Insect Physiology, Scientific Reports, Journal of Experimental Biology and Animal Behaviour.

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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