Jun Yao

3.9k citations
93 papers · 2.8k · h-index 27

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • RNA modifications and cancer
    • RNA and protein synthesis mechanisms
    • RNA Research and Splicing
    • Extracellular vesicles in disease

Papers in

    • RNA and protein synthesis mechanisms 15
    • RNA Research and Splicing 12
    • RNA modifications and cancer 12
    • CRISPR and Genetic Engineering 8
    • Bone Metabolism and Diseases 6

Jun Yao

90 papers receiving 2.8k citations

Peers

Jun Yao
Comparison fields: 5 of 133
  • Cancer Research 685
  • Molecular Biology 1.7k
  • Aquatic Science 177
  • Rheumatology 268
  • Immunology 345
Replace Tingting Wu with:
Tingting Wu China
Guillaume J.J.M. van Eys Netherlands
Chris H.A. van de Lest Netherlands
Alejandro J. Yáñez Chile
Ping Yang China
Yuri Kim South Korea
Lane K. Christenson United States
Osamu Ishibashi Japan
Marco Fabbri Italy
Li‐xin Xiang China
Jun Yao relative to Tingting Wu China Tingting Wu's profile →
Citations per field
00.5×1.5×2.2×
Tingting Wu · 1×
Citations per year

Countries citing papers authored by Jun Yao

Since Specialization
Citations

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

Fields of papers citing papers by Jun Yao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 93 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008300
2 2017256
3 2016192
4 2019175
5 201996
6 201590
7 201587
8 200680
9 201675
10 201367
11 201466
12 201665
13 201361
14 201656
15 201953
16 201551
17 200746
18 201645
19 201644
20 201843

About Jun Yao

Jun Yao is a scholar working on Molecular Biology, Genetics, Cancer Research, Immunology and Ecology, having authored 93 papers that have together received 2.8k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (15 papers), RNA Research and Splicing (12 papers), RNA modifications and cancer (12 papers), Cancer-related molecular mechanisms research (11 papers), CRISPR and Genetic Engineering (8 papers), Aquaculture disease management and microbiota (8 papers), Bacteriophages and microbial interactions (6 papers) and Bone Metabolism and Diseases (6 papers). The work is most often cited by research in Cancer Research (685 citations), Molecular Biology (1.7k citations), Aquatic Science (177 citations), Rheumatology (268 citations) and Immunology (345 citations). Jun Yao has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Alan M. Lambowitz, Yidan Qin, Ryan M. Nottingham, Matthew J. Shurtleff, Morayma M. Temoche-Diaz, Randy Schekman, Douglas C. Wu, Shikai Liu, Zhanjiang Liu and Wenjing Xu. Their work appears in journals such as Fish & Shellfish Immunology, RNA, Scientific Reports, Journal of Cellular Physiology and PLoS Genetics.

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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