Linyu Shi

8.7k total citations · 3 hit papers
56 papers, 4.4k citations indexed

About

Linyu Shi is a scholar working on Molecular Biology, Genetics and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Linyu Shi has authored 56 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Molecular Biology, 11 papers in Genetics and 6 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Linyu Shi's work include CRISPR and Genetic Engineering (24 papers), Pluripotent Stem Cells Research (14 papers) and RNA and protein synthesis mechanisms (8 papers). Linyu Shi is often cited by papers focused on CRISPR and Genetic Engineering (24 papers), Pluripotent Stem Cells Research (14 papers) and RNA and protein synthesis mechanisms (8 papers). Linyu Shi collaborates with scholars based in China, United States and Slovenia. Linyu Shi's co-authors include Hui Yang, Albert W. Cheng, Chikdu Shivalila, Rudolf Jaenisch, Haoyi Wang, Jinsong Li, Guoliang Xu, Yarden Katz, Daniel Benjamin Dadon and Thorold W. Theunissen and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Linyu Shi

55 papers receiving 4.3k citations

Hit Papers

One-Step Generation of Mice Carrying Reporter and Conditi... 2011 2026 2016 2021 2013 2011 2013 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Linyu Shi China 24 3.9k 1.1k 324 293 275 56 4.4k
Meelad M. Dawlaty United States 21 5.3k 1.4× 1.4k 1.3× 194 0.6× 276 0.9× 314 1.1× 39 5.9k
Tomoji Mashimo Japan 32 2.4k 0.6× 1.1k 1.0× 381 1.2× 381 1.3× 112 0.4× 138 3.7k
Chikdu Shivalila United States 9 4.5k 1.2× 1.5k 1.4× 188 0.6× 238 0.8× 479 1.7× 14 5.0k
Pratiksha I. Thakore United States 17 4.8k 1.2× 1.2k 1.1× 158 0.5× 379 1.3× 386 1.4× 24 5.6k
Azusa Inoue Japan 26 5.5k 1.4× 1.5k 1.4× 831 2.6× 160 0.5× 255 0.9× 46 5.9k
Randall J. Platt Switzerland 20 3.5k 0.9× 798 0.7× 233 0.7× 289 1.0× 208 0.8× 40 4.5k
Yujing Li United States 24 4.3k 1.1× 1.1k 1.0× 800 2.5× 181 0.6× 94 0.3× 59 5.6k
Liangxue Lai China 35 3.3k 0.9× 1.5k 1.4× 380 1.2× 106 0.4× 123 0.4× 136 4.0k
Niels Geijsen Netherlands 30 3.4k 0.9× 766 0.7× 630 1.9× 352 1.2× 97 0.4× 66 4.6k
Christopher M. Vockley United States 15 3.0k 0.8× 645 0.6× 92 0.3× 145 0.5× 214 0.8× 18 3.3k

Countries citing papers authored by Linyu Shi

Since Specialization
Citations

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

Fields of papers citing papers by Linyu Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Linyu Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Linyu Shi. A scholar is included among the top collaborators of Linyu Shi 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 Linyu Shi. Linyu Shi 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
2.
Yang, Dong, Xiaoqing Wu, Yinan Yao, et al.. (2024). An RNA editing strategy rescues gene duplication in a mouse model of MECP2 duplication syndrome and nonhuman primates. Nature Neuroscience. 28(1). 72–83. 6 indexed citations
3.
Yang, Dong, Yu Zhang, Qingquan Xiao, et al.. (2024). Adenine base editing-mediated exon skipping restores dystrophin in humanized Duchenne mouse model. Nature Communications. 15(1). 5927–5927. 15 indexed citations
4.
Tong, Huawei, Haoqiang Wang, Xuchen Wang, et al.. (2024). Development of deaminase-free T-to-S base editor and C-to-G base editor by engineered human uracil DNA glycosylase. Nature Communications. 15(1). 4897–4897. 30 indexed citations
5.
Yan, Zixiang, Xiaoqing Wu, Meng Zhang, et al.. (2023). Ptbp1 knockdown failed to induce astrocytes to neurons in vivo. Gene Therapy. 30(12). 801–806. 14 indexed citations
6.
Tong, Huawei, Nana Liu, Yinghui Wei, et al.. (2023). Programmable deaminase-free base editors for G-to-Y conversion by engineered glycosylase. National Science Review. 10(8). nwad143–nwad143. 45 indexed citations
7.
Wang, Xing, Dong Yang, Guoling Li, et al.. (2023). Develop a Compact RNA Base Editor by Fusing ADAR with Engineered EcCas6e. Advanced Science. 10(17). e2206813–e2206813. 20 indexed citations
8.
Kong, Xiangfeng, Hainan Zhang, Guoling Li, et al.. (2023). Engineered CRISPR-OsCas12f1 and RhCas12f1 with robust activities and expanded target range for genome editing. Nature Communications. 14(1). 2046–2046. 59 indexed citations
9.
Shi, Linyu, et al.. (2022). Does Cyberostracism Reduce Prosocial Behaviors? The Protective Role of Psychological Resilience. International Journal of Environmental Research and Public Health. 19(7). 4388–4388. 7 indexed citations
10.
Gao, Ni, Jing Hu, Bingbing He, et al.. (2021). Endogenous promoter-driven sgRNA for monitoring the expression of low-abundance transcripts and lncRNAs. Nature Cell Biology. 23(1). 99–108. 13 indexed citations
11.
Jia, Juan, Xu Liu, Fang Chen, et al.. (2021). Development and validation of a multiplex 19 X-chromosomal short tandem repeats typing system for forensic purposes. Scientific Reports. 11(1). 609–609. 10 indexed citations
12.
Zhou, Changyang, Xinde Hu, Cheng Tang, et al.. (2020). CasRx-mediated RNA targeting prevents choroidal neovascularization in a mouse model of age-related macular degeneration. National Science Review. 7(5). 835–837. 43 indexed citations
13.
Liu, Zhiyong, Linlin Gao, Jingjing Zhang, et al.. (2020). DNA typing from skeletal remains: a comparison between capillary electrophoresis and massively parallel sequencing platforms. International Journal of Legal Medicine. 134(6). 2029–2035. 2 indexed citations
14.
Yao, Xuan, Meiling Zhang, Xing Wang, et al.. (2018). Tild-CRISPR Allows for Efficient and Precise Gene Knockin in Mouse and Human Cells. Developmental Cell. 45(4). 526–536.e5. 108 indexed citations
15.
Zuo, Erwei, Xuan Yao, Xinde Hu, et al.. (2017). CRISPR/Cas9-mediated targeted chromosome elimination. Genome biology. 18(1). 224–224. 139 indexed citations
16.
Geng, Jiefei, Yasushi Ito, Linyu Shi, et al.. (2017). Regulation of RIPK1 activation by TAK1-mediated phosphorylation dictates apoptosis and necroptosis. Nature Communications. 8(1). 359–359. 239 indexed citations
18.
Yang, Hui, Haoyi Wang, Albert W. Cheng, et al.. (2013). One-Step Generation of Mice Carrying Reporter and Conditional Alleles by CRISPR/Cas-Mediated Genome Engineering. DSpace@MIT (Massachusetts Institute of Technology). 2 indexed citations
19.
Yang, Hui, Zhen Liu, Yu Ma, et al.. (2013). Generation of haploid embryonic stem cells from Macaca fascicularis monkey parthenotes. Cell Research. 23(10). 1187–1200. 86 indexed citations
20.
Yang, Hui, Linyu Shi, Bang-An Wang, et al.. (2012). Generation of Genetically Modified Mice by Oocyte Injection of Androgenetic Haploid Embryonic Stem Cells. Cell. 149(3). 605–617. 141 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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