Yaming Shao

1.7k total citations
22 papers, 911 citations indexed

About

Yaming Shao is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Cellular and Molecular Neuroscience. According to data from OpenAlex, Yaming Shao has authored 22 papers receiving a total of 911 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 6 papers in Cardiology and Cardiovascular Medicine and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Yaming Shao's work include RNA and protein synthesis mechanisms (12 papers), CRISPR and Genetic Engineering (7 papers) and Viral Infections and Immunology Research (6 papers). Yaming Shao is often cited by papers focused on RNA and protein synthesis mechanisms (12 papers), CRISPR and Genetic Engineering (7 papers) and Viral Infections and Immunology Research (6 papers). Yaming Shao collaborates with scholars based in United States, China and Israel. Yaming Shao's co-authors include Hong Li, Chuan‐Xi Zhang, Michael P. Terns, Nancy Ramia, Alexis Cocozaki, Ke Dong, Caryn Hale, Rebecca M. Terns, Joseph A. Piccirilli and Scott M. Stagg and has published in prestigious journals such as Angewandte Chemie International Edition, Nature Communications and Molecular Cell.

In The Last Decade

Yaming Shao

22 papers receiving 904 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yaming Shao United States	16	673	196	167	164	113	22	911
Hisato Hirano Japan	9	1.2k 1.8×	113 0.6×	114 0.7×	76 0.5×	60 0.5×	14	1.3k
A. Masuda Brazil	16	308 0.5×	144 0.7×	162 1.0×	145 0.9×	29 0.3×	26	843
Balázs Szöőr United Kingdom	19	625 0.9×	145 0.7×	120 0.7×	567 3.5×	50 0.4×	36	1.1k
Marieke R. Beijer Netherlands	7	522 0.8×	155 0.8×	76 0.5×	66 0.4×	40 0.4×	7	686
Jingjing Wang China	13	259 0.4×	128 0.7×	44 0.3×	66 0.4×	84 0.7×	56	589
Antonio M. Estévez Spain	23	927 1.4×	87 0.4×	105 0.6×	805 4.9×	249 2.2×	38	1.4k
J. van den Burg Netherlands	18	1.3k 2.0×	77 0.4×	110 0.7×	800 4.9×	141 1.2×	33	1.7k
Szu‐Yuan Pu United States	15	320 0.5×	121 0.6×	70 0.4×	120 0.7×	19 0.2×	24	848
Nikolay G. Kolev United States	17	749 1.1×	93 0.5×	164 1.0×	657 4.0×	133 1.2×	29	1.1k
Tansy C. Hammarton United Kingdom	19	485 0.7×	62 0.3×	161 1.0×	761 4.6×	45 0.4×	26	1.1k

Countries citing papers authored by Yaming Shao

Since Specialization

Citations

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

Fields of papers citing papers by Yaming Shao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yaming Shao

This figure shows the co-authorship network connecting the top 25 collaborators of Yaming Shao. A scholar is included among the top collaborators of Yaming Shao 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 Yaming Shao. Yaming Shao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Liu, Di, Yaming Shao, Joseph A. Piccirilli, & Yossi Weizmann. (2021). Structures of artificially designed discrete RNA nanoarchitectures at near-atomic resolution. Science Advances. 7(39). eabf4459–eabf4459. 3 indexed citations

Liu, Di, Cody Geary, Gang Chen, et al.. (2020). Branched kissing loops for the construction of diverse RNA homooligomeric nanostructures. Nature Chemistry. 12(3). 249–259. 53 indexed citations

Koirala, Deepak, Yaming Shao, Yelena Koldobskaya, et al.. (2019). A conserved RNA structural motif for organizing topology within picornaviral internal ribosome entry sites. Nature Communications. 10(1). 3629–3629. 18 indexed citations

Shelke, Sandip A., Yaming Shao, Deepak Koirala, et al.. (2018). Structural basis for activation of fluorogenic dyes by an RNA aptamer lacking a G-quadruplex motif. Nature Communications. 9(1). 38 indexed citations

Liu, Di, Yaming Shao, Gang Chen, et al.. (2017). Synthesizing topological structures containing RNA. Nature Communications. 8(1). 14936–14936. 25 indexed citations

Shao, Yaming, Hao Huang, Daoming Qin, et al.. (2016). Specific Recognition of a Single-Stranded RNA Sequence by a Synthetic Antibody Fragment. Journal of Molecular Biology. 428(20). 4100–4114. 10 indexed citations

Shao, Yaming, Hagen Richter, Kundan Sharma, et al.. (2016). A Non-Stem-Loop CRISPR RNA Is Processed by Dual Binding Cas6. Structure. 24(4). 547–554. 17 indexed citations

Wu, Jianjun, Wenwei Li, Yaming Shao, et al.. (2015). Inhibition of cGAS DNA Sensing by a Herpesvirus Virion Protein. Cell Host & Microbe. 18(3). 333–344. 236 indexed citations

Shao, Yaming, Shuichi Hoshika, Zunyi Yang, et al.. (2015). A Crystal Structure of a Functional RNA Molecule Containing an Artificial Nucleobase Pair. Angewandte Chemie International Edition. 54(34). 9853–9856. 18 indexed citations

10.

Ma, Yiyi, Katherine L. Tucker, Caren E. Smith, et al.. (2014). Lipoprotein lipase variants interact with polyunsaturated fatty acids for obesity traits in women: Replication in two populations. Nutrition Metabolism and Cardiovascular Diseases. 24(12). 1323–1329. 11 indexed citations

11.

Ramia, Nancy, Michael Spilman, Li Tang, et al.. (2014). Essential Structural and Functional Roles of the Cmr4 Subunit in RNA Cleavage by the Cmr CRISPR-Cas Complex. Cell Reports. 9(5). 1610–1617. 51 indexed citations

12.

Spilman, Michael, Alexis Cocozaki, Caryn Hale, et al.. (2013). Structure of an RNA Silencing Complex of the CRISPR-Cas Immune System. Molecular Cell. 52(1). 146–152. 105 indexed citations

13.

Shao, Yaming & Hong Li. (2013). Recognition and Cleavage of a Nonstructured CRISPR RNA by Its Processing Endoribonuclease Cas6. Structure. 21(3). 385–393. 39 indexed citations

14.

Shao, Yaming, Alexis Cocozaki, Nancy Ramia, et al.. (2013). Structure of the Cmr2-Cmr3 Subcomplex of the Cmr RNA Silencing Complex. Structure. 21(3). 376–384. 37 indexed citations

15.

Cocozaki, Alexis, Nancy Ramia, Yaming Shao, et al.. (2012). Structure of the Cmr2 Subunit of the CRISPR-Cas RNA Silencing Complex. Structure. 20(3). 545–553. 61 indexed citations

16.

Wang, Ruiying, et al.. (2012). The impact of CRISPR repeat sequence on structures of a Cas6 protein–RNA complex. Protein Science. 21(3). 405–417. 26 indexed citations

17.

Shao, Yaming, et al.. (2008). Molecular characterization of a sodium channel gene from the Silkworm Bombyx mori. Insect Biochemistry and Molecular Biology. 39(2). 145–151. 19 indexed citations

18.

Ge, Jun, et al.. (2008). Characterization of an early gene orf122 from Bombyx mori nucleopolyhedrovirus. Molecular Biology Reports. 36(3). 543–548. 7 indexed citations

19.

Shao, Yaming, Ke Dong, & Chuan‐Xi Zhang. (2007). The nicotinic acetylcholine receptor gene family of the silkworm, Bombyx mori. BMC Genomics. 8(1). 324–324. 83 indexed citations

20.

Shao, Yaming, et al.. (2007). Expression of two types of acetylcholinesterase gene from the silkworm, Bombyx mori, in insect cells. Insect Science. 14(6). 443–449. 40 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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