Cong Yi

4.6k total citations · 2 hit papers
28 papers, 1.2k citations indexed

About

Cong Yi is a scholar working on Epidemiology, Molecular Biology and Cell Biology. According to data from OpenAlex, Cong Yi has authored 28 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Epidemiology, 13 papers in Molecular Biology and 10 papers in Cell Biology. Recurrent topics in Cong Yi's work include Autophagy in Disease and Therapy (22 papers), Endoplasmic Reticulum Stress and Disease (6 papers) and Calcium signaling and nucleotide metabolism (5 papers). Cong Yi is often cited by papers focused on Autophagy in Disease and Therapy (22 papers), Endoplasmic Reticulum Stress and Disease (6 papers) and Calcium signaling and nucleotide metabolism (5 papers). Cong Yi collaborates with scholars based in China, United States and Hong Kong. Cong Yi's co-authors include Qiming Sun, Ayaz Najafov, Xufeng Cen, Hongguang Xia, Qingwei Zhao, Haiteng Deng, Yigang Wang, Yuting Cao, Fang Huang and Huihui Liu and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Cong Yi

25 papers receiving 1.2k citations

Hit Papers

CCT2 is an aggrephagy receptor for clearance of solid pro... 2022 2026 2023 2024 2022 2023 40 80 120

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cong Yi China 14 698 606 200 160 97 28 1.2k
Kostoula Troulinaki Greece 9 756 1.1× 757 1.2× 213 1.1× 136 0.8× 86 0.9× 10 1.4k
Wei‐Chung Chiang United States 11 940 1.3× 810 1.3× 207 1.0× 259 1.6× 144 1.5× 13 1.7k
Lidia Wróbel United Kingdom 15 988 1.4× 517 0.9× 330 1.6× 205 1.3× 68 0.7× 20 1.5k
Sarah F. Funderburk United States 6 441 0.6× 645 1.1× 241 1.2× 143 0.9× 51 0.5× 6 951
Jaganmohan R. Jangamreddy Sweden 13 698 1.0× 412 0.7× 155 0.8× 234 1.5× 150 1.5× 20 1.4k
Séverine Lorin France 12 624 0.9× 528 0.9× 168 0.8× 92 0.6× 118 1.2× 16 1.0k
Allyson L. Anding United States 8 437 0.6× 451 0.7× 212 1.1× 91 0.6× 52 0.5× 11 824
Ha‐Na Woo South Korea 18 830 1.2× 428 0.7× 180 0.9× 378 2.4× 130 1.3× 38 1.5k
Ian Semple United States 13 637 0.9× 386 0.6× 233 1.2× 157 1.0× 50 0.5× 13 1.0k
Orane Visvikis France 14 962 1.4× 826 1.4× 365 1.8× 278 1.7× 102 1.1× 20 1.9k

Countries citing papers authored by Cong Yi

Since Specialization
Citations

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

Fields of papers citing papers by Cong Yi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cong Yi

This figure shows the co-authorship network connecting the top 25 collaborators of Cong Yi. A scholar is included among the top collaborators of Cong Yi 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 Cong Yi. Cong Yi 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.
Zhao, Pengwei, Rui Tian, Xianming Ding, et al.. (2025). Rab GTPases are evolutionarily conserved signals mediating selective autophagy. The Journal of Cell Biology. 224(5).
2.
Zhang, Yi, et al.. (2025). Mec1-mediated Atg9 phosphorylation regulates the PAS recruitment of Atg9 vesicles upon energy stress. Proceedings of the National Academy of Sciences. 122(6). e2422582122–e2422582122. 1 indexed citations
3.
Zhang, Yi, Choufei Wu, Zhengyi Cai, et al.. (2025). Establishment of a yeast essential protein conditional-degradation library and screening for autophagy-regulating genes. Autophagy. 21(7). 1578–1590. 1 indexed citations
4.
Yi, Cong, et al.. (2025). Co-development of career adaptability and academic self-efficacy in college: A four-wave investigation. Journal of Applied Developmental Psychology. 98. 101792–101792. 2 indexed citations
5.
Chen, Yuting, Juan Song, Huan Yang, et al.. (2024). Two distinct regulatory pathways govern Cct2-Atg8 binding in the process of solid aggrephagy. EMBO Reports. 25(11). 4749–4776.
6.
Feng, Yuyao, et al.. (2024). The molecular mechanisms regulating the assembly of the autophagy initiation complex. BioEssays. 46(6). e2300243–e2300243. 3 indexed citations
7.
Yi, Cong, et al.. (2024). Energy deprivation-induced autophagy and aggrephagy: insights from yeast and mammals. Journal of Zhejiang University SCIENCE B. 25(12). 1066–1070.
8.
Feng, Yuyao, Ying Chen, Junye Chen, et al.. (2023). Interplay of energy metabolism and autophagy. Autophagy. 20(1). 4–14. 92 indexed citations breakdown →
9.
Ma, Xinyu, Yuting Chen, Shulin Li, et al.. (2022). CCT2 is an aggrephagy receptor for clearance of solid protein aggregates. Cell. 185(8). 1325–1345.e22. 120 indexed citations breakdown →
10.
Xu, Xiaoyan, Yaqin Sun, Xufeng Cen, et al.. (2021). Metformin activates chaperone-mediated autophagy and improves disease pathologies in an Alzheimer disease mouse model. Protein & Cell. 12(10). 769–787. 121 indexed citations
11.
Rao, Xi, Yin Shi, Lin Shi, et al.. (2021). AMPK-mediated phosphorylation enhances the auto-inhibition of TBC1D17 to promote Rab5-dependent glucose uptake. Cell Death and Differentiation. 28(12). 3214–3234. 23 indexed citations
12.
Wu, Choufei, Shuzhen Li, Liefeng Wang, et al.. (2020). Mitochondrial Fusion Machinery Specifically Involved in Energy Deprivation-Induced Autophagy. Frontiers in Cell and Developmental Biology. 8. 221–221. 11 indexed citations
13.
Wang, Yigang, Huihui Liu, Yuting Cao, et al.. (2020). The Role of Mitochondrial Dynamics and Mitophagy in Carcinogenesis, Metastasis and Therapy. Frontiers in Cell and Developmental Biology. 8. 413–413. 108 indexed citations
14.
Cen, Xufeng, Yanying Chen, Xiaoyan Xu, et al.. (2020). Pharmacological targeting of MCL-1 promotes mitophagy and improves disease pathologies in an Alzheimer’s disease mouse model. Nature Communications. 11(1). 5731–5731. 153 indexed citations
15.
Zhang, Ying, Yubin Xie, Wenzhong Liu, et al.. (2019). DeepPhagy: a deep learning framework for quantitatively measuring autophagy activity in Saccharomyces cerevisiae. Autophagy. 16(4). 626–640. 17 indexed citations
16.
Li, Terytty Yang, Lintao Song, Yu Sun, et al.. (2018). Tip60-mediated lipin 1 acetylation and ER translocation determine triacylglycerol synthesis rate. Nature Communications. 9(1). 1916–1916. 53 indexed citations
17.
Wan, Wei, Zhiyuan You, Li Zhou, et al.. (2018). mTORC1-Regulated and HUWE1-Mediated WIPI2 Degradation Controls Autophagy Flux. Molecular Cell. 72(2). 303–315.e6. 91 indexed citations
18.
Yi, Cong, Jingjing Tong, Yizheng Wang, et al.. (2017). Formation of a Snf1-Mec1-Atg1 Module on Mitochondria Governs Energy Deprivation-Induced Autophagy by Regulating Mitochondrial Respiration. Developmental Cell. 41(1). 59–71.e4. 61 indexed citations
19.
Yi, Cong, Meisheng Ma, Leili Ran, et al.. (2012). Function and Molecular Mechanism of Acetylation in Autophagy Regulation. Science. 336(6080). 474–477. 203 indexed citations
20.
Yi, Cong & Li Yu. (2012). How does acetylation regulate autophagy?. Autophagy. 8(10). 1529–1530. 18 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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