Song Li
Impact in
- Immunology and Allergy top 5%
- Cell Adhesion Molecules Research
- Cell Biology top 5%
- Cellular Mechanics and Interactions
Papers in
-
- CRISPR and Genetic Engineering 7
-
- Advanced Vision and Imaging 9
- Advanced Image Processing Techniques 7
- Image and Signal Denoising Methods 4
- Advanced Data Compression Techniques 3
- Co-authors
- Shu Chien (3 shared papers)Shunichi Usami (2 shared papers)Bauer E. Sumpio (1 shared paper)Nobuyoshi Azuma (1 shared paper)Ying‐Li Hu (1 shared paper)Xiong Wang (1 shared paper)Anthony Ratcliffe (1 shared paper)Yi‐Shuan Li (1 shared paper)
- Journals
- Foods (2 papers)Journal of Materials Engineering and Performance (2 papers)Applied Microbiology and Biotechnology (1 paper)Acta Pharmaceutica Sinica B (1 paper)Physical Review Research (1 paper)
- Partner nations
- ChinaUnited StatesFrance
In The Last Decade
Song Li
51 papers receiving 880 citations
Peers
Comparison fields: 5 of 123
- Immunology and Allergy 105
- Cell Biology 236
- Molecular Biology 441
- Aging 7
- Business and International Management 7
Countries citing papers authored by Song Li
This map shows the geographic impact of Song Li'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 Song Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Song Li more than expected).
Fields of papers citing papers by Song Li
This network shows the impact of papers produced by Song Li. 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 Song Li. The network helps show where Song Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Song Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1999 | 166 | |
| 2 | 2004 | 122 | |
| 3 | 2001 | 122 | |
| 4 | 2020 | 53 | |
| 5 | 2018 | 41 | |
| 6 | 2022 | 38 | |
| 7 | 2023 | 25 | |
| 8 | 2019 | 23 | |
| 9 | 2013 | 22 | |
| 10 | 2023 | 21 | |
| 11 | 2024 | 18 | |
| 12 | 2023 | 17 | |
| 13 | 2017 | 16 | |
| 14 | 2019 | 15 | |
| 15 | 2024 | 13 | |
| 16 | 2022 | 13 | |
| 17 | 2015 | 13 | |
| 18 | 2023 | 12 | |
| 19 | 2022 | 12 | |
| 20 | 2018 | 11 |
About Song Li
Song Li is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Biomedical Engineering, Materials Chemistry and Signal Processing, having authored 57 papers that have together received 895 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (9 papers), Advanced Image Processing Techniques (7 papers), CRISPR and Genetic Engineering (7 papers), Video Coding and Compression Technologies (4 papers), Image and Signal Denoising Methods (4 papers), Spectroscopy and Quantum Chemical Studies (3 papers), Advanced Data Compression Techniques (3 papers) and Material Dynamics and Properties (2 papers). The work is most often cited by research in Immunology and Allergy (105 citations), Cell Biology (236 citations), Molecular Biology (441 citations), Aging (7 citations) and Business and International Management (7 citations). Song Li has collaborated with scholars based in China, United States and France. Frequent co-authors include Shu Chien, Shunichi Usami, Bauer E. Sumpio, Nobuyoshi Azuma, Ying‐Li Hu, Xiong Wang, Anthony Ratcliffe, Yi‐Shuan Li, Martin A. Schwartz and Micah Dembo. Their work appears in journals such as Foods, Journal of Materials Engineering and Performance, Applied Microbiology and Biotechnology, Acta Pharmaceutica Sinica B and Physical Review Research.
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.