Kun Wei

534 citations
30 papers · 360 · h-index 11

Impact in

Papers in

    • Genetic and phenotypic traits in livestock 9
    • Genetic diversity and population structure 6
    • Genetic Mapping and Diversity in Plants and Animals 3
    • Molecular Biology Techniques and Applications 3

Kun Wei

27 papers receiving 352 citations

Peers

Kun Wei
Comparison fields: 5 of 81
  • Immunology 93
  • Animal Science and Zoology 39
  • Molecular Medicine 17
  • Genetics 86
  • Oncology 69
Replace Julia H Wildschutte with:
Julia H Wildschutte United States
Hsin‐Yiu Chou Taiwan
Haidong Xu China
O. S. Morenkov Russia
Bhavana Tiwari India
Shuyi Han China
Noriyuki HORIUCHI Japan
Reinhard Ertl Austria
Kristine M. Hope United States
Ferguson United Kingdom
Kun Wei relative to Julia H Wildschutte United States Julia H Wildschutte's profile →
Citations per field
00.5×
Julia H Wildschutte · 1×
Citations per year

Countries citing papers authored by Kun Wei

Since Specialization
Citations

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

Fields of papers citing papers by Kun Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202370
2 202345
3 201038
4 201929
5 201021
6 201019
7 200717
8 200916
9 202412
10 201111
11 200711
12 20188
13 20077
14 20087
15 20187
16 20187
17 20126
18 20066
19 20075
20
A novel method for sex determination of giant panda
20073

About Kun Wei

Kun Wei is a scholar working on Genetics, Molecular Biology, Immunology, Nature and Landscape Conservation and Ecology, having authored 30 papers that have together received 360 indexed citations. Recurring topics across this work include Genetic and phenotypic traits in livestock (9 papers), Genetic diversity and population structure (6 papers), Wildlife Ecology and Conservation (3 papers), CAR-T cell therapy research (3 papers), Molecular Biology Techniques and Applications (3 papers), Immune Cell Function and Interaction (3 papers), Genetic Mapping and Diversity in Plants and Animals (3 papers) and Immunotherapy and Immune Responses (3 papers). The work is most often cited by research in Immunology (93 citations), Animal Science and Zoology (39 citations), Molecular Medicine (17 citations), Genetics (86 citations) and Oncology (69 citations). Kun Wei has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Bisong Yue, Wenping Zhang, Zhihe Zhang, Fujun Shen, Hongning Wang, Xiaohong Zhao, Xiao Xu, Qinli Sun, Ling Ni and Chen Dong. Their work appears in journals such as Zoo Biology, Drug Discovery Today, Conservation Genetics, The Plant Journal and BMC Biology.

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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