Wu Dai

1.2k citations
89 papers · 886 · h-index 17

Impact in

Papers in

Wu Dai

82 papers receiving 850 citations

Peers

Wu Dai
Comparison fields: 5 of 55
  • Insect Science 479
  • Horticulture 23
  • Ecology, Evolution, Behavior and Systematics 364
  • Plant Science 508
  • Cellular and Molecular Neuroscience 133
Replace Andy Michel with:
Andy Michel United States
Jesus F. Esquivel United States
Wendy L. Meyer United States
Eduardo Gonçalves Paterson Fox Brazil
Dhana Raj Boina United States
Pierre Fouillet France
Ya‐Jun Gong China
G. Bonnot France
Gary J. R. Judd Canada
Anne Le Ralec France
Wu Dai relative to Andy Michel United States Andy Michel's profile →
Citations per field
00.5×4.8×
Andy Michel · 1×
Citations per year

Countries citing papers authored by Wu Dai

Since Specialization
Citations

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

Fields of papers citing papers by Wu Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 89 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201749
2 201047
3 201645
4 201738
5 201832
6 201931
7 201629
8 202225
9 201323
10 202323
11 202122
12 201221
13 201721
14 201920
15 201319
16 202319
17 202017
18 201216
19 202115
20 201615

About Wu Dai

Wu Dai is a scholar working on Plant Science, Ecology, Evolution, Behavior and Systematics, Insect Science, Molecular Biology and Genetics, having authored 89 papers that have together received 886 indexed citations. Recurring topics across this work include Phytoplasmas and Hemiptera pathogens (62 papers), Insect-Plant Interactions and Control (30 papers), Hymenoptera taxonomy and phylogeny (18 papers), Fossil Insects in Amber (14 papers), Plant and Fungal Species Descriptions (11 papers), Insect Resistance and Genetics (11 papers), Genomics and Phylogenetic Studies (10 papers) and Hemiptera Insect Studies (10 papers). The work is most often cited by research in Insect Science (479 citations), Horticulture (23 citations), Ecology, Evolution, Behavior and Systematics (364 citations), Plant Science (508 citations) and Cellular and Molecular Neuroscience (133 citations). Wu Dai has collaborated with scholars based in China, United States and Poland. Frequent co-authors include Chris H. Dietrich, Chunni Zhang, Yalin Zhang, Jolanta Brożek, Yan Wang, Bowen Tang, C. A. Viraktamath, Sindhu M. Krishnankutty, Michael D. Webb and Beibei Zhang. Their work appears in journals such as Zootaxa, Insects, Journal of Agricultural and Food Chemistry, Pesticide Biochemistry and Physiology and Arthropod Structure & Development.

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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