Jun Yao

4.3k total citations · 2 hit papers
89 papers, 2.8k citations indexed

About

Jun Yao is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Jun Yao has authored 89 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Molecular Biology, 28 papers in Cancer Research and 22 papers in Oncology. Recurrent topics in Jun Yao's work include MicroRNA in disease regulation (14 papers), Cancer-related molecular mechanisms research (12 papers) and Circular RNAs in diseases (9 papers). Jun Yao is often cited by papers focused on MicroRNA in disease regulation (14 papers), Cancer-related molecular mechanisms research (12 papers) and Circular RNAs in diseases (9 papers). Jun Yao collaborates with scholars based in China, United States and United Kingdom. Jun Yao's co-authors include David M. Stern, Cuijuan Qian, Xi Chen, Shi Du Yan, Ning Wang, Joyce W. Lustbader, Hong Xu, Casper Caspersen, Guy M. McKhann and Alexander A. Sosunov and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and Journal of Neuroscience.

In The Last Decade

Jun Yao

82 papers receiving 2.8k citations

Hit Papers

Mitochondrial Aβ: a potential focal point for neuronal me... 2005 2026 2012 2019 2005 2024 200 400 600

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 26 1.6k 954 482 423 295 89 2.8k
Stavit Drori Israel 15 2.0k 1.2× 936 1.0× 433 0.9× 352 0.8× 147 0.5× 22 3.3k
Julie C. Holder United Kingdom 23 2.3k 1.4× 761 0.8× 266 0.6× 300 0.7× 279 0.9× 32 3.3k
Tommaso Mello Italy 34 1.3k 0.8× 468 0.5× 471 1.0× 340 0.8× 161 0.5× 90 3.4k
Zhou Zhu China 32 1.8k 1.1× 500 0.5× 885 1.8× 481 1.1× 238 0.8× 93 3.6k
Daret St. Clair United States 21 1.5k 0.9× 452 0.5× 470 1.0× 574 1.4× 131 0.4× 51 2.8k
Chu Chang Chua United States 29 1.6k 1.0× 555 0.6× 337 0.7× 362 0.9× 159 0.5× 48 3.3k
Balvin H.L. Chua United States 39 2.5k 1.5× 754 0.8× 349 0.7× 345 0.8× 203 0.7× 68 4.6k
Evangeline D. Motley United States 32 2.0k 1.2× 715 0.7× 331 0.7× 223 0.5× 175 0.6× 45 3.2k
Shaoyu Zhou China 30 1.7k 1.1× 373 0.4× 339 0.7× 707 1.7× 206 0.7× 57 3.2k
Ana P. Gomes United States 22 1.7k 1.1× 792 0.8× 370 0.8× 537 1.3× 136 0.5× 48 3.1k

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.
Yang, H. B., Jun Yao, & Bing Du. (2025). Knowledge graph-based intelligent control systems for real-time machine tool optimization. Journal of Advanced Mechanical Design Systems and Manufacturing. 19(1). JAMDSM0013–JAMDSM0013.
2.
Hu, Wei, et al.. (2024). Learning spatiotemporal dependencies using adaptive hierarchical graph convolutional neural network for air quality prediction. Journal of Cleaner Production. 459. 142541–142541. 14 indexed citations
3.
Li, Jiangshan, Jun Yao, Xiao Zhang, et al.. (2024). Understanding the unique Ohmic-junction for enhancing the photocatalytic activity of CoS2/MgIn2S4 towards hydrogen production. Applied Catalysis B: Environmental. 351. 123950–123950. 83 indexed citations breakdown →
4.
Yao, Jun, et al.. (2024). Bi-LSTM/GRU-based anomaly diagnosis for virtual network function instance. Computer Networks. 249. 110515–110515. 6 indexed citations
5.
Zhang, Dianbao, et al.. (2024). Immune checkpoint inhibitor retreatment in second-line treatment of esophageal cancer: A real-world study.. Journal of Clinical Oncology. 42(16_suppl). e16034–e16034.
6.
Liu, Yun, et al.. (2024). Infection of Helicobacter pylori contributes to the progression of gastric cancer through ferroptosis. Cell Death Discovery. 10(1). 485–485. 4 indexed citations
8.
Yan, Jing, et al.. (2023). Circ_0002395 promotes aerobic glycolysis and proliferation in pancreatic adenocarcinoma cells via miR-548c-3p/PDK1 axis. Journal of Bioenergetics and Biomembranes. 56(1). 55–71. 3 indexed citations
9.
Chen, Yan‐Xing, Zixian Wang, Ying Jin, et al.. (2023). An immunogenic and oncogenic feature-based classification for chemotherapy plus PD-1 blockade in advanced esophageal squamous cell carcinoma. Cancer Cell. 41(5). 919–932.e5. 22 indexed citations
10.
Xiong, Xianqiang, Ngie Hing Wong, Lusi Ernawati, et al.. (2023). Revealing the enhanced photoelectrochemical water oxidation activity of Fe-based metal-organic polymer-modified BiVO4 photoanode. Journal of Colloid and Interface Science. 644. 533–545. 13 indexed citations
11.
Qian, Cuijuan, et al.. (2022). Circ_0000705 facilitates proline metabolism of esophageal squamous cell carcinoma cells by targeting miR-621/PYCR1 axis. Discover Oncology. 13(1). 50–50. 2 indexed citations
12.
Qian, Cuijuan, et al.. (2020). <p>LncRNA MAFG-AS1 Accelerates Cell Migration, Invasion and Aerobic Glycolysis of Esophageal Squamous Cell Carcinoma Cells via miR-765/PDX1 Axis</p>. Cancer Management and Research. Volume 12. 6895–6908. 21 indexed citations
13.
Shi, Yan, Tao Wang, Yong Zhou, et al.. (2019). MicroRNA-219a-5p suppresses intestinal inflammation through inhibiting Th1/Th17-mediated immune responses in inflammatory bowel disease. Mucosal Immunology. 13(2). 303–312. 29 indexed citations
14.
Shi, Xiaodong, et al.. (2017). Determination of palbociclib by high performance liquid chromatography. SHILAP Revista de lepidopterología. 2 indexed citations
15.
Wang, Leiping, et al.. (2014). Risk factors of post-traumatic hydrocephalus after decompressive craniectomy for patients with craniocerebral trauma. Zhonghua chuangshang zazhi. 30(4). 307–310. 3 indexed citations
17.
Qian, Cuijuan, Fuqiang Liu, Bei Ye, et al.. (2014). Notch4 promotes gastric cancer growth through activation of Wnt1/β-catenin signaling. Molecular and Cellular Biochemistry. 401(1-2). 165–174. 31 indexed citations
18.
Yao, Jun, Cuijuan Qian, Bei Ye, Xin Zhang, & Yong Liang. (2012). ERK inhibition enhances TSA-induced gastric cancer cell apoptosis via NF-κB-dependent and Notch-independent mechanism. Life Sciences. 91(5-6). 186–193. 23 indexed citations
19.
Yao, Jun. (2010). Expression of survivin and caspase-3 in gastric cancer and its clinical significance. Zhongguo aizheng zazhi.
20.
Duan, Li, Jun Yao, Xinxing Wu, & Mingwen Fan. (2006). Growth suppression induced by Notch1 activation involves Wnt—β‐catenin down‐regulation in human tongue carcinoma cells. Biology of the Cell. 98(8). 479–490. 59 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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