Gan Song

53 total papers · 458 total citations
20 papers, 303 citations indexed

About

Gan Song is a scholar working on Infectious Diseases, Automotive Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Gan Song has authored 20 papers receiving a total of 303 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Infectious Diseases, 6 papers in Automotive Engineering and 6 papers in Electrical and Electronic Engineering. Recurrent topics in Gan Song's work include Viral Infections and Vectors (6 papers), Advanced Battery Technologies Research (6 papers) and Viral Infections and Outbreaks Research (4 papers). Gan Song is often cited by papers focused on Viral Infections and Vectors (6 papers), Advanced Battery Technologies Research (6 papers) and Viral Infections and Outbreaks Research (4 papers). Gan Song collaborates with scholars based in China, United States and Malaysia. Gan Song's co-authors include Tingran Zhang, Jiong Luo, Kun Wang, Li Peng, Heping Ling, Yubo Lian, Bin He, Changshou Hang, Tao Hung and Xiǎohóng Shí and has published in prestigious journals such as The Lancet, Environmental Science & Technology and Frontiers in Psychology.

In The Last Decade

Gan Song

15 papers receiving 287 citations

Author Peers

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

Author						Papers	Cites
Gan Song	136	84	51	45	40	20	303
Francesca Mazzoli	55 0.4×	6 0.1×	56 1.1×	92 2.0×	59 1.5×	18	249
Amy Green	87 0.6×	6 0.1×	52 1.0×	39 0.9×	146 3.6×	15	328
Wayne Adams	31 0.2×	6 0.1×	52 1.0×	29 0.6×	26 0.7×	19	302
Michael C. Goates	10 0.1×	16 0.2×	31 0.6×	46 1.0×	28 0.7×	22	294
Manahil Siddiqi	24 0.2×	11 0.1×	37 0.7×	111 2.5×	27 0.7×	19	327
Andrea Jelić	8 0.1×	14 0.2×	9 0.2×	130 2.9×	16 0.4×	18	365
Jiasheng Huang	24 0.2×	3 0.0×	112 2.2×	64 1.4×	12 0.3×	25	307
Jason B. Reed	13 0.1×	10 0.1×	11 0.2×	21 0.5×	43 1.1×	35	235
Bill Jenkins	13 0.1×	3 0.0×	18 0.4×	64 1.4×	37 0.9×	13	349
Michael J. Penkunas	7 0.1×	10 0.1×	17 0.3×	95 2.1×	37 0.9×	25	277

Countries citing papers authored by Gan Song

Since Specialization

Citations

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

Fields of papers citing papers by Gan Song

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gan Song

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