Jin Su Song

1.5k total citations
43 papers, 1.1k citations indexed

About

Jin Su Song is a scholar working on Infectious Diseases, Molecular Biology and Epidemiology. According to data from OpenAlex, Jin Su Song has authored 43 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Infectious Diseases, 13 papers in Molecular Biology and 10 papers in Epidemiology. Recurrent topics in Jin Su Song's work include Mass Spectrometry Techniques and Applications (5 papers), Advanced Proteomics Techniques and Applications (5 papers) and Tuberculosis Research and Epidemiology (4 papers). Jin Su Song is often cited by papers focused on Mass Spectrometry Techniques and Applications (5 papers), Advanced Proteomics Techniques and Applications (5 papers) and Tuberculosis Research and Epidemiology (4 papers). Jin Su Song collaborates with scholars based in South Korea, United States and Ethiopia. Jin Su Song's co-authors include Hie-Joon Kim, Pil Joon Seo, Mi Jung Kim, Chung‐Mo Park, Jeong Hill Park, Soon‐Sun Hong, Sung Won Kwon, Seo Young Lee, Mijeong Park and Se Won Suh and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Analytical Biochemistry.

In The Last Decade

Jin Su Song

42 papers receiving 1.1k citations

Peers

Jin Su Song
Comparison fields: 5 of 103
  • Molecular Biology 491
  • Infectious Diseases 304
  • Epidemiology 210
  • Plant Science 169
  • Immunology 103
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Citations per field, relative to Jin Su Song
Jin Su Song · 1×
Citations per year, relative to Jin Su Song
Jin Su Song · 1×

Countries citing papers authored by Jin Su Song

Since Specialization
Citations

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

Fields of papers citing papers by Jin Su Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jin Su Song

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 9
3 1
4 6
5 3
6 6
7 10
8
Effects of Glucosidorum Tripterygll Totorum Tablet on Serum HMGB1 and IL-17 in Rats with Collagen-induced Arthritis
1
9 6
10 17
11 17
12 1
13 19
14 13
15 12
16 45
17 108
18 8
19
Multicenter Study for Frequency and Clinical Features of Community-Associated Methicillin-Resistant Staphylococcus aureus in Korea
8
20
Malignancies in Patients with Human Immunodeficiency Virus Infection in South Korea
5

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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