Jun Yao

3.9k total citations
93 papers, 2.8k citations indexed

About

Jun Yao is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Jun Yao has authored 93 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Molecular Biology, 19 papers in Genetics and 18 papers in Cancer Research. Recurrent topics in Jun Yao's work include RNA and protein synthesis mechanisms (15 papers), RNA modifications and cancer (12 papers) and RNA Research and Splicing (12 papers). Jun Yao is often cited by papers focused on RNA and protein synthesis mechanisms (15 papers), RNA modifications and cancer (12 papers) and RNA Research and Splicing (12 papers). Jun Yao collaborates with scholars based in China, United States and Australia. Jun Yao's co-authors include Alan M. Lambowitz, Yidan Qin, Ryan M. Nottingham, Randy Schekman, Morayma M. Temoche-Diaz, Matthew J. Shurtleff, Douglas C. Wu, Shikai Liu, Zhanjiang Liu and Shenguo Wang and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Jun Yao

90 papers receiving 2.8k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jun Yao China 27 1.7k 685 386 345 268 93 2.8k
Anna Bassols Spain 29 1.4k 0.8× 329 0.5× 372 1.0× 178 0.5× 114 0.4× 120 3.3k
Alejandro J. Yáñez Chile 27 960 0.6× 319 0.5× 241 0.6× 942 2.7× 83 0.3× 120 2.7k
Tingting Wu China 31 1.4k 0.8× 762 1.1× 289 0.7× 721 2.1× 121 0.5× 93 3.1k
Liliana Tatarczuch Australia 19 831 0.5× 234 0.3× 334 0.9× 529 1.5× 556 2.1× 36 2.3k
Yuri Kim South Korea 18 2.1k 1.2× 467 0.7× 284 0.7× 259 0.8× 102 0.4× 40 3.4k
Chris H.A. van de Lest Netherlands 35 1.1k 0.7× 326 0.5× 179 0.5× 277 0.8× 644 2.4× 98 3.5k
Guillaume J.J.M. van Eys Netherlands 27 1.2k 0.7× 171 0.2× 146 0.4× 270 0.8× 71 0.3× 49 2.8k
Shuo Huang China 26 1.6k 0.9× 388 0.6× 395 1.0× 306 0.9× 174 0.6× 78 2.9k
Richard G. Taylor United States 30 1.4k 0.8× 181 0.3× 252 0.7× 541 1.6× 48 0.2× 90 3.5k

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-authorship network of co-authors of Jun Yao

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Yao. A scholar is included among the top collaborators of Jun Yao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jun Yao. Jun Yao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wu, Tingting, G. Chen, Jun Yao, et al.. (2025). Muscle strength trajectories and outcomes in critically ill patients: A prospective multicentre cohort study. Intensive and Critical Care Nursing. 88. 103934–103934. 1 indexed citations
2.
Mohr, Georg, et al.. (2024). Mechanisms used for cDNA synthesis and site-specific integration of RNA into DNA genomes by a reverse transcriptase–Cas1 fusion protein. Science Advances. 10(15). eadk8791–eadk8791. 1 indexed citations
3.
4.
Colgan, Thomas J., Zhengyi Zhang, Fugang Liu, et al.. (2023). Unexpected worker mating and colony-founding in a superorganism. Nature Communications. 14(1). 5499–5499. 5 indexed citations
5.
Xu, Haoming, Jing Xu, Min‐zheng Zhu, et al.. (2023). Therapeutic potential of gene therapy for gastrointestinal diseases: Advancements and future perspectives. Molecular Therapy — Oncolytics. 30. 193–215. 4 indexed citations
6.
Yao, Jun, Long Su, Xiaomeng Zhao, et al.. (2023). Pan‐genome analysis highlights the role of structural variation in the evolution and environmental adaptation of Asian honeybees. Molecular Ecology Resources. 24(2). e13905–e13905. 7 indexed citations
7.
Xu, Peng, Jun Yao, Zhongrui Li, et al.. (2020). Therapeutic Effect of Doxorubicin-Chlorin E6-Loaded Mesoporous Silica Nanoparticles Combined with Ultrasound on Triple-Negative Breast Cancer. SHILAP Revista de lepidopterología. 1 indexed citations
8.
Wang, Huang, Jian Li, Ye Cheng, & Jun Yao. (2020). Association of Long-Chain Noncoding RNA H19 and MEG3 Gene Polymorphisms and Their Interaction with Risk of Osteoarthritis in a Chinese Han Population. Genetic Testing and Molecular Biomarkers. 24(6). 328–337. 10 indexed citations
9.
Mohr, Georg, et al.. (2018). A Highly Proliferative Group IIC Intron from Geobacillus stearothermophilus Reveals New Features of Group II Intron Mobility and Splicing. Journal of Molecular Biology. 430(17). 2760–2783. 11 indexed citations
10.
Mohr, Georg, Sukrit Silas, Jennifer L. Stamos, et al.. (2018). A Reverse Transcriptase-Cas1 Fusion Protein Contains a Cas6 Domain Required for Both CRISPR RNA Biogenesis and RNA Spacer Acquisition. Molecular Cell. 72(4). 700–714.e8. 21 indexed citations
11.
Zhong, Gang, Ruiming Liang, Jun Yao, et al.. (2018). Artemisinin Ameliorates Osteoarthritis by Inhibiting the Wnt/β-Catenin Signaling Pathway. Cellular Physiology and Biochemistry. 51(6). 2575–2590. 34 indexed citations
12.
Shurtleff, Matthew J., Jun Yao, Yidan Qin, et al.. (2017). Broad role for YBX1 in defining the small noncoding RNA composition of exosomes. Proceedings of the National Academy of Sciences. 114(43). E8987–E8995. 256 indexed citations
13.
14.
Nottingham, Ryan M., Douglas C. Wu, Yidan Qin, et al.. (2016). RNA-seq of human reference RNA samples using a thermostable group II intron reverse transcriptase. RNA. 22(4). 597–613. 65 indexed citations
15.
Fu, Qiang, Qifan Zeng, Yun Li, et al.. (2016). The chemokinome superfamily in channel catfish: I. CXC subfamily and their involvement in disease defense and hypoxia responses. Fish & Shellfish Immunology. 60. 380–390. 44 indexed citations
16.
Wang, Fang, et al.. (2014). MicroRNA-29b Regulates TGF-β1-Mediated Epithelial-Mesenchymal Transition of Retinal Pigment Epithelial Cells by Targeting AKT2. Investigative Ophthalmology & Visual Science. 55(13). 4994–4994. 33 indexed citations
17.
Yao, Jun, et al.. (2013). Optimal effective concentration of ropivacaine for postoperative analgesia by single-shot femoral–sciatic nerve block in outpatient knee arthroscopy. Journal of International Medical Research. 41(2). 395–403. 13 indexed citations
18.
Jiang, Yan, Mary Qiu, Guigen Zhang, et al.. (2010). Quality assurance in the HIV/AIDS laboratory network of China. International Journal of Epidemiology. 39(Supplement 2). ii72–ii78. 22 indexed citations
19.
Cui, Xiaoxia, et al.. (2010). Genetic identification of potential RNA-binding regions in a group II intron-encoded reverse transcriptase. RNA. 16(4). 732–747. 21 indexed citations
20.
Shi, Bao, Feng He, Shuang Lin Dong, et al.. (2008). Association of reproductive performance with SNPs of FOXL2 gene by SSCP in Japanese flounder (Paralichthys olivaceus). Comparative Biochemistry and Physiology Part B Biochemistry and Molecular Biology. 153(1). 1–7. 12 indexed citations

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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