Weiming Ai

729 citations
61 papers · 578 · h-index 15

Impact in

Papers in

    • Identification and Quantification in Food 31
    • Genomics and Phylogenetic Studies 29
    • Molecular Biology Techniques and Applications 4
    • Ichthyology and Marine Biology 27
    • Fish Ecology and Management Studies 4

Weiming Ai

56 papers receiving 566 citations

Peers

Weiming Ai
Comparison fields: 5 of 95
  • Nature and Landscape Conservation 160
  • Aquatic Science 92
  • Pollution 81
  • Health, Toxicology and Mutagenesis 69
  • Immunology 101
Replace Zhongduo Wang with:
Zhongduo Wang China
Yusong Guo China
Christopher B. Rees United States
Bettina Zeis Germany
D. Costagliola Italy
Hongjian Lü China
Heather L. Walsh United States
André M. Machado Portugal
H.O.L. Mok Hong Kong
José Dias Corrêa Brazil
Weiming Ai relative to Zhongduo Wang China Zhongduo Wang's profile →
Citations per field
00.5×3.9×
Zhongduo Wang · 1×
Citations per year

Countries citing papers authored by Weiming Ai

Since Specialization
Citations

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

Fields of papers citing papers by Weiming Ai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201757
2 201355
3 201947
4 202033
5 201329
6 200527
7 201725
8 201224
9 201622
10 201718
11 201317
12 201217
13 202016
14 202416
15 201415
16 201613
17 202211
18 201310
19 20178
20 20148

About Weiming Ai

Weiming Ai is a scholar working on Molecular Biology, Nature and Landscape Conservation, Aquatic Science, Immunology and Cancer Research, having authored 61 papers that have together received 578 indexed citations. Recurring topics across this work include Identification and Quantification in Food (31 papers), Genomics and Phylogenetic Studies (29 papers), Ichthyology and Marine Biology (27 papers), Fish Biology and Ecology Studies (11 papers), Aquaculture disease management and microbiota (11 papers), Fish Ecology and Management Studies (4 papers), Molecular Biology Techniques and Applications (4 papers) and MicroRNA in disease regulation (4 papers). The work is most often cited by research in Nature and Landscape Conservation (160 citations), Aquatic Science (92 citations), Pollution (81 citations), Health, Toxicology and Mutagenesis (69 citations) and Immunology (101 citations). Weiming Ai has collaborated with scholars based in China, Hong Kong and Thailand. Frequent co-authors include Huili Wang, Shaobo Chen, Xuedong Wang, Xiao Chen, Dan Xiang, Shaobo Chen, Limei Sun, Yunyun Chen, Yuhuan Zhang and Xiaofang Shi. Their work appears in journals such as Environmental Pollution, Horticultural Plant Journal, The Science of The Total Environment, Comparative Biochemistry and Physiology Part C Toxicology & Pharmacology and PLoS ONE.

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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