Song Wu

44 total papers · 518 total citations
35 papers, 436 citations indexed

About

Song Wu is a scholar working on Complementary and alternative medicine, Pharmacology and Molecular Biology. According to data from OpenAlex, Song Wu has authored 35 papers receiving a total of 436 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Complementary and alternative medicine, 11 papers in Pharmacology and 8 papers in Molecular Biology. Recurrent topics in Song Wu's work include Acupuncture Treatment Research Studies (18 papers), Healthcare and Venom Research (11 papers) and Traditional Chinese Medicine Studies (10 papers). Song Wu is often cited by papers focused on Acupuncture Treatment Research Studies (18 papers), Healthcare and Venom Research (11 papers) and Traditional Chinese Medicine Studies (10 papers). Song Wu collaborates with scholars based in China and Hong Kong. Song Wu's co-authors include Tak‐Ming Wong, Jianming Pei, Xiao-Chun Yu, Guanying Wang, Tak Ming Wong, Gennadi M. Kravtsov, Jing Liu, Feng-Xia Liang, Jia Li and Jing‐Jun Zhou and has published in prestigious journals such as British Journal of Pharmacology, American Journal of Physiology-Heart and Circulatory Physiology and American Journal of Physiology-Cell Physiology.

In The Last Decade

Song Wu

33 papers receiving 428 citations

Author Peers

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

Author						Papers	Cites
Song Wu	170	142	119	87	78	35	436
Turhan Dost	158 0.9×	69 0.5×	142 1.2×	69 0.8×	24 0.3×	30	478
Rui‐Rong He	139 0.8×	59 0.4×	109 0.9×	57 0.7×	20 0.3×	59	377
Hadi Ebrahimi	82 0.5×	52 0.4×	103 0.9×	32 0.4×	75 1.0×	39	471
Arthur G. Williams	90 0.5×	177 1.2×	81 0.7×	73 0.8×	27 0.3×	35	494
Arkady Uryash	45 0.3×	131 0.9×	140 1.2×	43 0.5×	55 0.7×	39	458
Rong‐Rui Zhao	110 0.6×	183 1.3×	177 1.5×	54 0.6×	14 0.2×	30	439
J P Morgan	90 0.5×	182 1.3×	136 1.1×	47 0.5×	43 0.6×	21	449
S DIGERNESS	134 0.8×	234 1.6×	87 0.7×	62 0.7×	14 0.2×	24	421
Carmem Luíza Sartório	118 0.7×	187 1.3×	164 1.4×	30 0.3×	20 0.3×	30	479
Nobuhisa Uemura	105 0.6×	204 1.4×	93 0.8×	65 0.7×	15 0.2×	30	456

Countries citing papers authored by Song Wu

Since Specialization

Citations

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

Fields of papers citing papers by Song Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Song Wu

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