Su-Chun How
Impact in
- Biomaterials top 10%
- Nanoparticle-Based Drug Delivery
- Supramolecular Self-Assembly in Materials
- Physiology top 10%
- Alzheimer's disease research and treatments
Papers in
- Physiology 11
- Alzheimer's disease research and treatments 11
-
- Nanoparticle-Based Drug Delivery 2
- Nanocomposite Films for Food Packaging 2
- Co-authors
- Steven S.‐S. Wang (22 shared papers)Josephine W. Wu (7 shared papers)Ta-Hsien Lin (6 shared papers)Jan Jeng-Shiung (3 shared papers)Wei‐Lung Chou (4 shared papers)Chun‐Chao Chang (1 shared paper)Wei‐An Chen (2 shared papers)Chaur‐Jong Hu (1 shared paper)
In The Last Decade
Su-Chun How
27 papers receiving 450 citations
Peers
Comparison fields: 5 of 50
- Biomaterials 102
- Physiology 150
- Molecular Medicine 32
- Food Science 58
- Molecular Biology 175
Countries citing papers authored by Su-Chun How
This map shows the geographic impact of Su-Chun How'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 Su-Chun How with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Su-Chun How more than expected).
Fields of papers citing papers by Su-Chun How
This network shows the impact of papers produced by Su-Chun How. 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 Su-Chun How. The network helps show where Su-Chun How may publish in the future.
Co-authors
The 25 scholars most cited alongside Su-Chun How, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 66 | |
| 2 | 2021 | 37 | |
| 3 | 2017 | 36 | |
| 4 | 2023 | 29 | |
| 5 | 2016 | 28 | |
| 6 | 2016 | 26 | |
| 7 | 2018 | 25 | |
| 8 | 2018 | 25 | |
| 9 | 2017 | 23 | |
| 10 | 2020 | 17 | |
| 11 | 2015 | 16 | |
| 12 | 2022 | 16 | |
| 13 | 2023 | 15 | |
| 14 | 2020 | 14 | |
| 15 | 2019 | 12 | |
| 16 | 2024 | 11 | |
| 17 | 2021 | 9 | |
| 18 | 2024 | 9 | |
| 19 | 2022 | 8 | |
| 20 | 2018 | 7 |
About Su-Chun How
Su-Chun How is a scholar working on Physiology, Biomaterials, Molecular Biology, Water Science and Technology and Molecular Medicine, having authored 27 papers that have together received 454 indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (11 papers), Prion Diseases and Protein Misfolding (9 papers), Protein purification and stability (5 papers), Enzyme Catalysis and Immobilization (3 papers), Adsorption and biosorption for pollutant removal (3 papers), Nanoparticle-Based Drug Delivery (2 papers), Membrane Separation Technologies (2 papers) and Nanocomposite Films for Food Packaging (2 papers). The work is most often cited by research in Biomaterials (102 citations), Physiology (150 citations), Molecular Medicine (32 citations), Food Science (58 citations) and Molecular Biology (175 citations). Su-Chun How has collaborated with scholars based in Taiwan, Slovakia and Malaysia. Frequent co-authors include Steven S.‐S. Wang, Josephine W. Wu, Ta-Hsien Lin, Jan Jeng-Shiung, Wei‐Lung Chou, Chun‐Chao Chang, Wei‐An Chen, Chaur‐Jong Hu, Chia‐Ping Tseng and Kuan-Nan Liu. Their work appears in journals such as International Journal of Biological Macromolecules, Journal of the Taiwan Institute of Chemical Engineers, Colloids and Surfaces B Biointerfaces, Polymers and Membranes.
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.