Shuoyong Shi

1.0k total citations
9 papers, 668 citations indexed

About

Shuoyong Shi is a scholar working on Molecular Biology, Materials Chemistry and Pharmacology. According to data from OpenAlex, Shuoyong Shi has authored 9 papers receiving a total of 668 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 4 papers in Materials Chemistry and 1 paper in Pharmacology. Recurrent topics in Shuoyong Shi's work include Protein Structure and Dynamics (6 papers), RNA and protein synthesis mechanisms (4 papers) and Enzyme Structure and Function (4 papers). Shuoyong Shi is often cited by papers focused on Protein Structure and Dynamics (6 papers), RNA and protein synthesis mechanisms (4 papers) and Enzyme Structure and Function (4 papers). Shuoyong Shi collaborates with scholars based in United States, China and Switzerland. Shuoyong Shi's co-authors include Nick V. Grishin, Yuxing Liao, Lisa N. Kinch, Jimin Pei, Hua Cheng, R. Dustin Schaeffer, Bong-Hyun Kim, Klaus Brinkmann, Lisa Henry and Zhucheng Chen and has published in prestigious journals such as Cell, Bioinformatics and Journal of Molecular Biology.

In The Last Decade

Shuoyong Shi

9 papers receiving 663 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shuoyong Shi United States	9	558	170	106	69	57	9	668
András Aszódi Austria	15	694 1.2×	194 1.1×	60 0.6×	51 0.7×	72 1.3×	28	950
Chern-Sing Goh United States	10	784 1.4×	97 0.6×	68 0.6×	32 0.5×	104 1.8×	11	1.0k
Heike A. Held United States	9	669 1.2×	78 0.5×	238 2.2×	70 1.0×	38 0.7×	10	847
Pawel Smialowski Germany	15	1.1k 1.9×	146 0.9×	69 0.7×	95 1.4×	116 2.0×	27	1.2k
Ewa A. Bienkiewicz United States	13	548 1.0×	137 0.8×	59 0.6×	64 0.9×	34 0.6×	20	722
Michael A. Stiffler United States	10	794 1.4×	58 0.3×	161 1.5×	71 1.0×	189 3.3×	11	888
Élodie Monsellier France	12	657 1.2×	111 0.7×	152 1.4×	120 1.7×	63 1.1×	17	774
Brian J. Yeh United States	10	1.1k 1.9×	81 0.5×	198 1.9×	77 1.1×	122 2.1×	12	1.2k
Timothy J. Ragan United Kingdom	16	854 1.5×	70 0.4×	70 0.7×	134 1.9×	120 2.1×	26	1.1k
Éva Schád Hungary	16	936 1.7×	172 1.0×	177 1.7×	61 0.9×	100 1.8×	29	1.1k

Countries citing papers authored by Shuoyong Shi

Since Specialization

Citations

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

Fields of papers citing papers by Shuoyong Shi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuoyong Shi

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

All Works

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9 of 9 papers shown

1.

Chitturi, Bhadrachalam, Shuoyong Shi, Lisa N. Kinch, & Nick V. Grishin. (2016). Compact Structure Patterns in Proteins. Journal of Molecular Biology. 428(21). 4392–4412. 18 indexed citations

2.

Chen, Baoyu, Klaus Brinkmann, Zhucheng Chen, et al.. (2014). The WAVE Regulatory Complex Links Diverse Receptors to the Actin Cytoskeleton. Cell. 156(1-2). 195–207. 210 indexed citations

3.

Cheng, Hua, R. Dustin Schaeffer, Yuxing Liao, et al.. (2014). ECOD: An Evolutionary Classification of Protein Domains. PLoS Computational Biology. 10(12). e1003926–e1003926. 289 indexed citations

4.

Kinch, Lisa N., Shuoyong Shi, Hua Cheng, et al.. (2011). CASP9 target classification. Proteins Structure Function and Bioinformatics. 79(S10). 21–36. 60 indexed citations

5.

Cong, Qian, Lisa N. Kinch, Jimin Pei, et al.. (2011). An automatic method for CASP9 free modeling structure prediction assessment. Bioinformatics. 27(24). 3371–3378. 21 indexed citations

6.

Sadreyev, Ruslan I., Shuoyong Shi, David Baker, & Nick V. Grishin. (2009). Structure similarity measure with penalty for close non-equivalent residues. Bioinformatics. 25(10). 1259–1263. 13 indexed citations

7.

Shi, Shuoyong, et al.. (2007). Searching for three-dimensional secondary structural patterns in proteins with ProSMoS. Bioinformatics. 23(11). 1331–1338. 31 indexed citations

8.

Cai, Xiaohui, Qing Zhang, Shuoyong Shi, & Da-Fu Ding. (2005). Searching for Potential Drug Targets in Two-component and Phosphorelay Signal-transduction Systems using Three-dimensional Cluster Analysis. Acta Biochimica et Biophysica Sinica. 37(5). 293–302. 12 indexed citations

9.

Shi, Shuoyong, Xiaohui Cai, & Da-Fu Ding. (2005). Identification and Categorization of Horizontally Transferred Genes in Prokaryotic Genomes. Acta Biochimica et Biophysica Sinica. 37(8). 561–566. 14 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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