Min Song

550 citations
24 papers · 427 · h-index 11

Impact in

Papers in

    • HIV/AIDS drug development and treatment 5
    • SARS-CoV-2 detection and testing 3
    • SARS-CoV-2 and COVID-19 Research 2
    • RNA Interference and Gene Delivery 2

Min Song

24 papers receiving 419 citations

Peers

Min Song
Comparison fields: 5 of 74
  • Virology 113
  • Infectious Diseases 126
  • Agronomy and Crop Science 34
  • Molecular Medicine 16
  • Epidemiology 92
Replace Haifeng Song with:
Haifeng Song China
Jhen Tsang United Kingdom
Di Dai China
Chirag Dhar United States
Gongying Chen China
Heather Grieser United States
Sherko Nasseri Iran
Gudrun Stamminger Germany
Aloys Tijsma Belgium
Min Song relative to Haifeng Song China Haifeng Song's profile →
Citations per field
00.5×2×4×6×8.5×
Haifeng Song · 1×
Citations per year

Countries citing papers authored by Min Song

Since Specialization
Citations

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

Fields of papers citing papers by Min Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Min Song, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Min Song Line = papers co-authored together Min Song links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008106
2 201453
3 202437
4 200937
5 201829
6 201128
7 202222
8 201520
9 202114
10 200612
11 201411
12 20099
13 20229
14 20078
15 20208
16 20206
17 20224
18 20214
19 20253
20 20252

About Min Song

Min Song is a scholar working on Infectious Diseases, Molecular Biology, Virology, Surgery and Epidemiology, having authored 24 papers that have together received 427 indexed citations. Recurring topics across this work include HIV Research and Treatment (6 papers), HIV/AIDS drug development and treatment (5 papers), Antibiotic Resistance in Bacteria (3 papers), SARS-CoV-2 detection and testing (3 papers), RNA Interference and Gene Delivery (2 papers), Influenza Virus Research Studies (2 papers), Animal Disease Management and Epidemiology (2 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). The work is most often cited by research in Virology (113 citations), Infectious Diseases (126 citations), Agronomy and Crop Science (34 citations), Molecular Medicine (16 citations) and Epidemiology (92 citations). Min Song has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Robert A. Bambara, Lu Gao, Lirong Liang, Guohua Mao, Young Ki Choi, Zhipeng Zhu, Lisong Lin, Dali Zheng, Yong Zhao and Youguang Lu. Their work appears in journals such as Journal of Biological Chemistry, Cellular and Molecular Neurobiology, Journal of Clinical Microbiology, Environmental Science and Pollution Research and Molecular and Cellular Biochemistry.

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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