Chun Song
- Pulmonary and Respiratory Medicine
- Physiology
- Molecular Biology
- Organic Chemistry
- Cardiology and Cardiovascular Medicine
- Co-authors
- Shigefumi FujimuraSadafumi OnoSatoshi SuzukiTatsuo TanitaMasafumi NodaToshiharu TabataYasushi HoshikawaMasayuki Chida
- Topics
- Neutrophil, Myeloperoxidase and Oxidative Mechanisms (3 papers)Pulmonary Hypertension Research and Treatments (3 papers)S100 Proteins and Annexins (3 papers)
In The Last Decade
Chun Song
13 papers receiving 355 citations
Peers
Comparison fields: 5 of 74
- Pulmonary and Respiratory Medicine 158
- Physiology 78
- Molecular Biology 77
- Organic Chemistry 73
- Cardiology and Cardiovascular Medicine 58
Countries citing papers authored by Chun Song
This map shows the geographic impact of Chun 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 Chun Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chun Song more than expected).
Fields of papers citing papers by Chun Song
This network shows the impact of papers produced by Chun 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 Chun Song. The network helps show where Chun Song may publish in the future.
Co-authorship network of co-authors of Chun Song
This figure shows the co-authorship network connecting the top 25 collaborators of Chun Song. A scholar is included among the top collaborators of Chun 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 Chun Song. Chun Song is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 79 | |
| 2 | 23 | |
| 3 | 14 | |
| 4 | 195 | |
| 5 | 13 | |
| 6 | 4 | |
| 7 | 4 | |
| 8 | 4 | |
| 9 | 3 | |
| 10 | 1 | |
| 11 | [Role of leukotriene B4 in monocrotaline-induced pulmonary hypertension]. | 16 |
| 12 | [Increase in pulmonary vascular permeability caused by increased expression of Mac-1 on the surface of polymorphonuclear leukocytes]. | 0 |
| 13 | 1 | |
| 14 | [Effects of prostaglandin E1 (PGE1) on pulmonary hypertension and lung vascular remodeling in a rat monocrotaline model of human pulmonary hypertension]. | 4 |
About Chun Song
Chun Song is a scholar working on Pulmonary and Respiratory Medicine, Immunology and Allergy and Physiology, having authored 14 papers that have together received 361 indexed citations. Recurring topics across this work include Neutrophil, Myeloperoxidase and Oxidative Mechanisms (3 papers), Pulmonary Hypertension Research and Treatments (3 papers) and S100 Proteins and Annexins (3 papers). The work is most often cited by research in Endocrine and Autonomic Systems (34 citations), Pulmonary and Respiratory Medicine (158 citations) and Biochemistry (30 citations). Chun Song has collaborated with scholars based in Japan, Canada and China. Frequent co-authors include Shigefumi Fujimura, Sadafumi Ono, Satoshi Suzuki, Tatsuo Tanita, Masafumi Noda, Toshiharu Tabata, Yasushi Hoshikawa, Masayuki Chida, Norbert F. Voelkel and Guangchen Li. Their work appears in journals such as Journal of Applied Physiology, European Respiratory Journal and Thorax.
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.