Jun Yao

3.4k citations
186 papers · 2.6k · h-index 28

Impact in

Papers in

    • Molecular Biology Techniques and Applications 13
    • Receptor Mechanisms and Signaling 9
    • RNA Research and Splicing 8
    • Forensic and Genetic Research 19

Jun Yao

175 papers receiving 2.5k citations

Peers

Jun Yao
Comparison fields: 5 of 131
  • Sensory Systems 173
  • Biological Psychiatry 64
  • Biotechnology 176
  • Neurology 140
  • Molecular Biology 1.2k
Replace He Li with:
He Li China
Rammohan V. Rao United States
Glória Emília Petto de Souza Brazil
Chong Li China
Soraya S. Smaili Brazil
Hong Wei China
Biwen Peng China
Hyunkyoung Lee South Korea
Lucrezia Guida Italy
Connie R. Faltynek United States
Jun Yao relative to He Li China He Li's profile →
Citations per field
00.5×5.8×
He Li · 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 186 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201989
2 201583
3 202077
4 201771
5 201068
6 201163
7 201462
8 199762
9 200061
10 201452
11 201149
12 200845
13 200142
14 201041
15 201440
16 200839
17 201937
18 201936
19 201435
20 199734

About Jun Yao

Jun Yao is a scholar working on Molecular Biology, Genetics, Cellular and Molecular Neuroscience, Sensory Systems and Cancer Research, having authored 186 papers that have together received 2.6k indexed citations. Recurring topics across this work include Forensic and Genetic Research (19 papers), Hearing, Cochlea, Tinnitus, Genetics (14 papers), Molecular Biology Techniques and Applications (13 papers), Neuroscience and Neuropharmacology Research (12 papers), Neurotransmitter Receptor Influence on Behavior (11 papers), MicroRNA in disease regulation (10 papers), Receptor Mechanisms and Signaling (9 papers) and RNA Research and Splicing (8 papers). The work is most often cited by research in Sensory Systems (173 citations), Biological Psychiatry (64 citations), Biotechnology (176 citations), Neurology (140 citations) and Molecular Biology (1.2k citations). Jun Yao has collaborated with scholars based in China, United States and Saudi Arabia. Frequent co-authors include Garth F. Hall, Baojie Wang, Xin Cao, Qinjun Wei, Yajie Lu, Gloria Lee, Hong Xu, Guangqian Xing, Pingkai Ouyang and Xinming Qi. Their work appears in journals such as PLoS ONE, Journal of Molecular Neuroscience, Forensic Science International Genetics, International Journal of Legal Medicine and Journal of Translational Medicine.

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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