Song‐Shu Lin

49 total papers · 1.1k total citations
36 papers, 875 citations indexed

About

Song‐Shu Lin is a scholar working on Surgery, Genetics and Pathology and Forensic Medicine. According to data from OpenAlex, Song‐Shu Lin has authored 36 papers receiving a total of 875 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Surgery, 9 papers in Genetics and 8 papers in Pathology and Forensic Medicine. Recurrent topics in Song‐Shu Lin's work include Mesenchymal stem cell research (8 papers), Spine and Intervertebral Disc Pathology (8 papers) and Orthopedic Infections and Treatments (7 papers). Song‐Shu Lin is often cited by papers focused on Mesenchymal stem cell research (8 papers), Spine and Intervertebral Disc Pathology (8 papers) and Orthopedic Infections and Treatments (7 papers). Song‐Shu Lin collaborates with scholars based in Taiwan, United States and China. Song‐Shu Lin's co-authors include Steve Wen‐Neng Ueng, Li‐Jen Yuan, Shih‐Jung Liu, Wen‐Jer Chen, Chi‐Chien Niu, Ching‐Lung Tai, Chun‐Hsiung Shih, Jean‐Pierre Kinet, Hirohei Yamamura and Andrew M. Scharenberg and has published in prestigious journals such as The EMBO Journal, Spine and Clinical Orthopaedics and Related Research.

In The Last Decade

Song‐Shu Lin

36 papers receiving 855 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Song‐Shu Lin	293	182	140	139	136	36	875
Hae Chang Jeong	273 0.9×	264 1.5×	155 1.1×	67 0.5×	163 1.2×	33	908
B Schneider	294 1.0×	191 1.0×	55 0.4×	147 1.1×	86 0.6×	29	1.0k
Jason A. Horton	165 0.6×	276 1.5×	58 0.4×	261 1.9×	126 0.9×	45	962
Marc A. Soares	335 1.1×	223 1.2×	50 0.4×	55 0.4×	61 0.4×	29	950
J R Nash	241 0.8×	130 0.7×	140 1.0×	60 0.4×	24 0.2×	41	875
Yi Lu	99 0.3×	277 1.5×	143 1.0×	79 0.6×	162 1.2×	54	975
Laura S. Gregory	136 0.5×	181 1.0×	62 0.4×	105 0.8×	86 0.6×	35	714
Yuki Ishikawa	130 0.4×	365 2.0×	123 0.9×	379 2.7×	65 0.5×	37	1.0k
Martin Decaris	213 0.7×	201 1.1×	48 0.3×	34 0.2×	197 1.4×	34	834
Rebecca D. Levit	320 1.1×	184 1.0×	54 0.4×	61 0.4×	113 0.8×	32	795

Countries citing papers authored by Song‐Shu Lin

Since Specialization

Citations

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

Fields of papers citing papers by Song‐Shu Lin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Song‐Shu Lin. 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 Song‐Shu Lin. The network helps show where Song‐Shu Lin may publish in the future.

Co-authorship network of co-authors of Song‐Shu Lin

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

All Works

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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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