Jonathan C. Su
Impact in
- Biomaterials top 10%
- Silk-based biomaterials and applications
- Supramolecular Self-Assembly in Materials
- Electrospun Nanofibers in Biomedical Applications
- Computer Science Applications top 10%
- Teaching and Learning Programming
Papers in
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- RNA Research and Splicing 2
- Protein purification and stability 1
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- Teaching and Learning Programming 3
- Open Education and E-Learning 2
- Co-authors
- Ashutosh Chilkoti (3 shared papers)Anastasia K. Varanko (2 shared papers)Susan H. Rodger (3 shared papers)Eric Wiebe (2 shared papers)Ashutosh Chilkoti (2 shared papers)Yifan Dai (2 shared papers)Dongheon Lee (1 shared paper)Rohit V. Pappu (1 shared paper)
- Journals
- Nature Chemistry (1 paper)Diabetes (1 paper)Nature Communications (1 paper)Annual Review of Biomedical Engineering (1 paper)Nature Chemical Biology (1 paper)
- Partner nations
- United States
In The Last Decade
Jonathan C. Su
9 papers receiving 359 citations
Jonathan C. Su's Hit Papers
Peers
Comparison fields: 5 of 81
- Biomaterials 111
- Computer Science Applications 39
- Software 20
- Surfaces, Coatings and Films 24
- Molecular Medicine 15
Countries citing papers authored by Jonathan C. Su
This map shows the geographic impact of Jonathan C. Su'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 Jonathan C. Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan C. Su more than expected).
Fields of papers citing papers by Jonathan C. Su
This network shows the impact of papers produced by Jonathan C. Su. 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 Jonathan C. Su. The network helps show where Jonathan C. Su may publish in the future.
Co-authors
The 25 scholars most cited alongside Jonathan C. Su, 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 | 2020 | 195 | |
| 2 | Programmable synthetic biomolecular condensates for cellular control Hit paper breakdown → | 2023 | 89 |
| 3 | 2009 | 31 | |
| 4 | 2009 | 20 | |
| 5 | 2024 | 18 | |
| 6 | 2025 | 13 | |
| 7 | 2025 | 2 | |
| 8 | 2019 | 1 | |
| 9 | 2011 | 1 |
About Jonathan C. Su
Jonathan C. Su is a scholar working on Molecular Biology, Computer Science Applications, Software, Genetics and Surgery, having authored 9 papers that have together received 370 indexed citations. Recurring topics across this work include Software Testing and Debugging Techniques (3 papers), Teaching and Learning Programming (3 papers), Connective tissue disorders research (2 papers), RNA Research and Splicing (2 papers), Open Education and E-Learning (2 papers), Peptidase Inhibition and Analysis (1 paper), Pancreatic function and diabetes (1 paper) and Protein purification and stability (1 paper). The work is most often cited by research in Biomaterials (111 citations), Computer Science Applications (39 citations), Software (20 citations), Surfaces, Coatings and Films (24 citations) and Molecular Medicine (15 citations). Jonathan C. Su has collaborated with scholars based in United States. Frequent co-authors include Ashutosh Chilkoti, Anastasia K. Varanko, Susan H. Rodger, Eric Wiebe, Ashutosh Chilkoti, Yifan Dai, Dongheon Lee, Rohit V. Pappu, Lingchong You and Xiangze Zeng. Their work appears in journals such as Nature Chemistry, Diabetes, Nature Communications, Annual Review of Biomedical Engineering and Nature Chemical Biology.
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.