Yu Jiang

9.1k total citations
119 papers, 5.1k citations indexed

About

Yu Jiang is a scholar working on Molecular Biology, Cell Biology and Oncology. According to data from OpenAlex, Yu Jiang has authored 119 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 86 papers in Molecular Biology, 20 papers in Cell Biology and 18 papers in Oncology. Recurrent topics in Yu Jiang's work include PI3K/AKT/mTOR signaling in cancer (22 papers), Fungal and yeast genetics research (17 papers) and MicroRNA in disease regulation (11 papers). Yu Jiang is often cited by papers focused on PI3K/AKT/mTOR signaling in cancer (22 papers), Fungal and yeast genetics research (17 papers) and MicroRNA in disease regulation (11 papers). Yu Jiang collaborates with scholars based in United States, China and Australia. Yu Jiang's co-authors include Xiaochun Bai, James R. Broach, Susan Ferro‐Novick, Dongzhu Ma, Anling Liu, Gonghong Yan, Xiaoyun Shen, Yongjian Liu, Yumei Lai and Yin Zheng and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Yu Jiang

113 papers receiving 5.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yu Jiang United States 45 3.6k 1.0k 702 686 593 119 5.1k
Hidetoshi Hayashi Japan 30 3.2k 0.9× 970 1.0× 600 0.9× 572 0.8× 750 1.3× 131 5.2k
Danny N. Dhanasekaran United States 38 3.3k 0.9× 620 0.6× 540 0.8× 1.2k 1.7× 638 1.1× 107 5.2k
Kei Tobiume Japan 22 3.2k 0.9× 1.2k 1.2× 684 1.0× 804 1.2× 720 1.2× 45 4.6k
Jongsun Park South Korea 35 4.0k 1.1× 445 0.4× 463 0.7× 632 0.9× 591 1.0× 126 5.7k
Andrei V. Budanov United States 26 4.5k 1.3× 872 0.9× 1.1k 1.6× 1.0k 1.5× 930 1.6× 42 6.1k
Yongjun Dang China 33 3.3k 0.9× 496 0.5× 645 0.9× 724 1.1× 1.1k 1.8× 101 5.2k
Min Ni China 31 3.2k 0.9× 1.7k 1.7× 1.1k 1.5× 627 0.9× 613 1.0× 97 5.5k
Ching-Shih Chen United States 46 3.3k 0.9× 755 0.7× 345 0.5× 652 1.0× 920 1.6× 83 5.3k
Martin O. Bergö Sweden 41 5.0k 1.4× 889 0.9× 403 0.6× 927 1.4× 947 1.6× 106 6.8k
Mauricio J. Reginato United States 35 4.2k 1.2× 734 0.7× 647 0.9× 1.1k 1.6× 1.2k 2.0× 63 5.7k

Countries citing papers authored by Yu Jiang

Since Specialization
Citations

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

Fields of papers citing papers by Yu Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yu Jiang

This figure shows the co-authorship network connecting the top 25 collaborators of Yu Jiang. A scholar is included among the top collaborators of Yu Jiang 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 Yu Jiang. Yu Jiang 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.
Liao, Zhenrui, Yu Jiang, Fei Liang, et al.. (2025). Nanovaccine enables complement system inhibition and high-dose AAV re-administration. Chemical Engineering Journal. 507. 160810–160810. 1 indexed citations
2.
Zhou, Wu, Lihua Qiu, Zhanfeng Liang, et al.. (2025). Brown adipose tissue secretes OLFM4 to coordinate sensory and sympathetic innervation via Schwann cells. Nature Communications. 16(1). 5206–5206.
3.
Zhang, Jiayu, et al.. (2025). Glabridin Alleviates Metabolic Disorders in Diet‐Induced Diabetic Mice. Phytotherapy Research. 39(12). 5551–5566.
4.
Li, Yuexin, et al.. (2024). The application of extracellular vesicles in orthopedic diseases. SHILAP Revista de lepidopterología. 2(3). 23 indexed citations
5.
Yang, Lin, Doudou Wang, Zhixin Zhang, Yu Jiang, & Ying Liu. (2022). Isoliquiritigenin alleviates diabetic symptoms via activating AMPK and inhibiting mTORC1 signaling in diet-induced diabetic mice. Phytomedicine. 98. 153950–153950. 23 indexed citations
6.
Jiang, Yu, et al.. (2021). Silencing of the CrkL gene reverses the doxorubicin resistance of K562/ADR cells through regulating PI3K/Akt/MRP1 signaling. Journal of Clinical Laboratory Analysis. 35(8). e23817–e23817. 5 indexed citations
7.
Jiang, Yu, et al.. (2019). <p>miR-1271 inhibits growth, invasion and epithelial–mesenchymal transition by targeting ZEB1 in ovarian cancer cells</p>. OncoTargets and Therapy. Volume 12. 6973–6980. 14 indexed citations
8.
Yuan, Wenjie, et al.. (2017). General Control Nonderepressible 2 (GCN2) Kinase Inhibits Target of Rapamycin Complex 1 in Response to Amino Acid Starvation in Saccharomyces cerevisiae. Journal of Biological Chemistry. 292(7). 2660–2669. 49 indexed citations
9.
Long, Kimberly R., Youssef Rbaibi, Elizabeth V. Menshikova, et al.. (2017). Proximal tubule apical endocytosis is modulated by fluid shear stress via an mTOR-dependent pathway. Molecular Biology of the Cell. 28(19). 2508–2517. 46 indexed citations
10.
Gao, Jiaoqi, Wenjie Yuan, Yimin Li, Feng‐Wu Bai, & Yu Jiang. (2017). Synergistic effect of thioredoxin and its reductase from Kluyveromyces marxianus on enhanced tolerance to multiple lignocellulose-derived inhibitors. Microbial Cell Factories. 16(1). 181–181. 14 indexed citations
11.
Li, Liangpeng, Hong Liu, Yongchao Wang, et al.. (2013). Farnesoid X receptor up-regulates expression of Lipid transfer inhibitor protein in liver cells and mice. Biochemical and Biophysical Research Communications. 441(4). 880–885. 12 indexed citations
12.
Zou, Huafei, Yumei Lai, Gonghong Yan, et al.. (2013). Regulation of Mammalian Target of Rapamycin Complex 1 by Bcl-2 and Bcl-XL Proteins. Journal of Biological Chemistry. 288(40). 28824–28830. 16 indexed citations
13.
Wen, Zehuai, Yu‐Chieh Su, Yaqing Zhang, et al.. (2012). Critical role of arachidonic acid-activated mTOR signaling in breast carcinogenesis and angiogenesis. Oncogene. 32(2). 160–170. 80 indexed citations
14.
Ma, Liyuan, Lin Li, Yu Jiang, et al.. (2011). Youchasaponin induces apoptosis of human leukemia Jurkat cells in vitro and its possible mechanism. Tumori. 31(12). 1072–1076. 2 indexed citations
15.
Ma, Dongzhu, Xiaochun Bai, Huafei Zou, Yumei Lai, & Yu Jiang. (2010). Rheb GTPase Controls Apoptosis by Regulating Interaction of FKBP38 with Bcl-2 and Bcl-XL. Journal of Biological Chemistry. 285(12). 8621–8627. 44 indexed citations
16.
Bommareddy, Ajay, Dong Xiao, Anna A. Powolny, et al.. (2009). Atg5 Regulates Phenethyl Isothiocyanate–Induced Autophagic and Apoptotic Cell Death in Human Prostate Cancer Cells. Cancer Research. 69(8). 3704–3712. 132 indexed citations
17.
Bai, Xiaochun & Yu Jiang. (2009). Key factors in mTOR regulation. Cellular and Molecular Life Sciences. 67(2). 239–253. 103 indexed citations
18.
Bai, Xiaochun, Dongzhu Ma, Anling Liu, et al.. (2007). Rheb Activates mTOR by Antagonizing Its Endogenous Inhibitor, FKBP38. Science. 318(5852). 977–980. 301 indexed citations
19.
Jiang, Yu. (2006). The Effects of Prenatal and Postnatal Lead Exposure on Children Intelligence. Huanjing yu zhiye yixue. 2 indexed citations
20.
Zheng, Yin & Yu Jiang. (2005). The Yeast Phosphotyrosyl Phosphatase Activator Is Part of the Tap42–Phosphatase Complexes. Molecular Biology of the Cell. 16(4). 2119–2127. 31 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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