Shujun Song

47 total papers · 1.1k total citations
32 papers, 937 citations indexed

About

Shujun Song is a scholar working on Molecular Biology, Cancer Research and Pathology and Forensic Medicine. According to data from OpenAlex, Shujun Song has authored 32 papers receiving a total of 937 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 6 papers in Cancer Research and 5 papers in Pathology and Forensic Medicine. Recurrent topics in Shujun Song's work include Blood Coagulation and Thrombosis Mechanisms (5 papers), Nanoplatforms for cancer theranostics (4 papers) and Protease and Inhibitor Mechanisms (4 papers). Shujun Song is often cited by papers focused on Blood Coagulation and Thrombosis Mechanisms (5 papers), Nanoplatforms for cancer theranostics (4 papers) and Protease and Inhibitor Mechanisms (4 papers). Shujun Song collaborates with scholars based in China, Australia and Singapore. Shujun Song's co-authors include Shaoyan Si, Robert N. Pike, Charles N. Pagel, Eleanor J. Mackie, Kai Feng, Jun‐Li Liu, Junli Liu, Simon M. Cool, Victor Nurcombe and Yanchuan Guo and has published in prestigious journals such as ACS Nano, PLoS ONE and ACS Applied Materials & Interfaces.

In The Last Decade

Shujun Song

31 papers receiving 913 citations

Author Peers

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

Author						Papers	Cites
Shujun Song	268	217	164	117	112	32	937
Adrian Băican	228 0.9×	265 1.2×	103 0.6×	95 0.8×	57 0.5×	32	1.2k
Dan Chen	346 1.3×	64 0.3×	120 0.7×	74 0.6×	183 1.6×	56	998
Minjun Huang	257 1.0×	102 0.5×	27 0.2×	113 1.0×	58 0.5×	56	826
Anna Neve	499 1.9×	142 0.7×	30 0.2×	176 1.5×	109 1.0×	16	1.2k
Katja Lakota	351 1.3×	197 0.9×	43 0.3×	54 0.5×	92 0.8×	72	1.1k
S. F. Wotton	323 1.2×	352 1.6×	65 0.4×	73 0.6×	174 1.6×	28	1.2k
P. García	174 0.6×	50 0.2×	75 0.5×	164 1.4×	27 0.2×	34	976
Takashi Saito	238 0.9×	37 0.2×	44 0.3×	152 1.3×	55 0.5×	70	1.1k
Richard Le Naour	323 1.2×	90 0.4×	47 0.3×	32 0.3×	134 1.2×	45	1.1k
Tatjana Odrljin	212 0.8×	57 0.3×	66 0.4×	110 0.9×	56 0.5×	30	1.0k

Countries citing papers authored by Shujun Song

Since Specialization

Citations

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

Fields of papers citing papers by Shujun Song

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shujun Song

This figure shows the co-authorship network connecting the top 25 collaborators of Shujun Song. A scholar is included among the top collaborators of Shujun Song 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 Shujun Song. Shujun Song 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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