Jun Xia

2.6k citations
70 papers · 1.6k · h-index 22

Impact in

Papers in

    • Genomics and Phylogenetic Studies 12
    • Physiological and biochemical adaptations 6
    • Microbial Community Ecology and Physiology 6

Jun Xia

67 papers receiving 1.6k citations

Peers

Jun Xia
Comparison fields: 5 of 111
  • Aquatic Science 410
  • Immunology 483
  • Ecology 417
  • Genetics 347
  • Cancer Research 127
Replace Motoshige Yasuike with:
Motoshige Yasuike Japan
Qiaozhen Ke China
Zi Yi Wan Singapore
Futoshi Aranishi Japan
Lanjie Liao China
A. E. Tinch United Kingdom
Sebastián Boltaña Chile
Qian Gao China
Wilaiwan Chotigeat Thailand
Belén G. Pardo Spain
Jun Xia relative to Motoshige Yasuike Japan Motoshige Yasuike's profile →
Citations per field
00.5×3.7×
Motoshige Yasuike · 1×
Citations per year

Countries citing papers authored by Jun Xia

Since Specialization
Citations

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

Fields of papers citing papers by Jun Xia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014254
2 2000105
3 2011102
4 201572
5 201354
6 201749
7 201847
8 201546
9 201044
10 201344
11 201744
12 201439
13 201438
14 202037
15 201436
16 201835
17 201032
18 201730
19 200929
20 201729

About Jun Xia

Jun Xia is a scholar working on Molecular Biology, Ecology, Genetics, Immunology and Aquatic Science, having authored 70 papers that have together received 1.6k indexed citations. Recurring topics across this work include Aquaculture disease management and microbiota (17 papers), Genomics and Phylogenetic Studies (12 papers), Aquaculture Nutrition and Growth (11 papers), Genetic diversity and population structure (7 papers), Genetic and phenotypic traits in livestock (6 papers), Physiological and biochemical adaptations (6 papers), Microbial Community Ecology and Physiology (6 papers) and Genetic Mapping and Diversity in Plants and Animals (5 papers). The work is most often cited by research in Aquatic Science (410 citations), Immunology (483 citations), Ecology (417 citations), Genetics (347 citations) and Cancer Research (127 citations). Jun Xia has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Gen Hua Yue, Grace Lin, Zi Yi Wan, Le Wang, Hao Lin, Xiaojun Liu, May Lee, Hong Lian Li, Bi Jun Li and Shu‐Sheng Liu. Their work appears in journals such as Aquaculture, Marine Biotechnology, PLoS ONE, BMC Genomics and INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY.

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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