Yabing Song
Impact in
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- Antifungal resistance and susceptibility
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- Complement system in diseases
- T-cell and B-cell Immunology
Papers in
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- Animal Virus Infections Studies 2
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- Antifungal resistance and susceptibility 3
- Co-authors
- Jianbin Wang (9 shared papers)Jiaxin Gao (5 shared papers)Eve W. L. Chow (4 shared papers)Xiaoli Xu (3 shared papers)H Joe Wang (2 shared papers)Xin Liu (1 shared paper)Jiacheng Yao (1 shared paper)Chengshuo Wang (1 shared paper)
In The Last Decade
Yabing Song
16 papers receiving 247 citations
Yabing Song's Hit Papers
Peers
Comparison fields: 5 of 24
- Infectious Diseases 42
- Immunology 23
- Molecular Biology 65
- Cardiology and Cardiovascular Medicine 20
- Otorhinolaryngology 4
Countries citing papers authored by Yabing Song
This map shows the geographic impact of Yabing 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 Yabing Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yabing Song more than expected).
Fields of papers citing papers by Yabing Song
This network shows the impact of papers produced by Yabing 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 Yabing Song. The network helps show where Yabing Song may publish in the future.
Co-authors
The 25 scholars most cited alongside Yabing Song, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 61 | |
| 2 | GZMK-expressing CD8+ T cells promote recurrent airway inflammatory diseases Hit paper breakdown → | 2025 | 58 |
| 3 | 2021 | 35 | |
| 4 | 2023 | 30 | |
| 5 | 2023 | 15 | |
| 6 | 2023 | 10 | |
| 7 | 2015 | 9 | |
| 8 | 2023 | 9 | |
| 9 | 2024 | 7 | |
| 10 | 2022 | 5 | |
| 11 | 2023 | 4 | |
| 12 | 2006 | 3 | |
| 13 | 2025 | 2 | |
| 14 | 2025 | 1 | |
| 15 | 2026 | 1 | |
| 16 | 2026 | 1 | |
| 17 | Epidemiological survey and analysis of porcine deltacoronavirus in Guangdong province from 2012 to 2016. | 2018 | 0 |
About Yabing Song
Yabing Song is a scholar working on Animal Science and Zoology, Infectious Diseases, Molecular Biology, Otorhinolaryngology and Management, Monitoring, Policy and Law, having authored 17 papers that have together received 251 indexed citations. Recurring topics across this work include Antifungal resistance and susceptibility (3 papers), Animal Virus Infections Studies (2 papers), Congenital heart defects research (2 papers), Sinusitis and nasal conditions (1 paper), Fungal and yeast genetics research (1 paper), Landslides and related hazards (1 paper), Cervical and Thoracic Myelopathy (1 paper) and Genomics and Phylogenetic Studies (1 paper). The work is most often cited by research in Infectious Diseases (42 citations), Immunology (23 citations), Molecular Biology (65 citations), Cardiology and Cardiovascular Medicine (20 citations) and Otorhinolaryngology (4 citations). Yabing Song has collaborated with scholars based in China, Singapore and Macao. Frequent co-authors include Jianbin Wang, Jiaxin Gao, Eve W. L. Chow, Xiaoli Xu, H Joe Wang, Xin Liu, Jiacheng Yao, Chengshuo Wang, Luo Zhang and Feng Lan. Their work appears in journals such as Nature Microbiology, npj Regenerative Medicine, BMC Bioinformatics, Developmental Cell and Journal of Orthopaedic Translation.
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.