Shuke Wu
Impact in
- Molecular Biology top 5%
- Enzyme Catalysis and Immobilization
- Microbial Metabolic Engineering and Bioproduction
- Chemical Synthesis and Analysis
- Organic Chemistry top 2%
Papers in ⓘ
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- Pharmacogenetics and Drug Metabolism 6
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- Enzyme Catalysis and Immobilization 33
- Microbial Metabolic Engineering and Bioproduction 25
- Chemical Synthesis and Analysis 5
- Steroid Chemistry and Biochemistry 4
- Co-authors
- Uwe T. Bornscheuer (17 shared papers)Zhi Li (20 shared papers)Radka Šnajdrová (5 shared papers)Kai Baldenius (4 shared papers)Jeffrey C. Moore (2 shared papers)Yi Zhou (14 shared papers)Christoffel P. S. Badenhorst (5 shared papers)Thomas Bayer (6 shared papers)
In The Last Decade
Shuke Wu
44 papers receiving 2.9k citations
Hit Papers
Peers
Comparison fields: 5 of 96
- Molecular Biology 2.3k
- Organic Chemistry 733
- Inorganic Chemistry 351
- Biochemistry 179
- Pharmacology 191
Countries citing papers authored by Shuke Wu
This map shows the geographic impact of Shuke Wu'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 Shuke Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuke Wu more than expected).
Fields of papers citing papers by Shuke Wu
This network shows the impact of papers produced by Shuke Wu. 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 Shuke Wu. The network helps show where Shuke Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Shuke Wu, 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 46 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Biocatalysis: Enzymatic Synthesis for Industrial Applications Hit paper breakdown → | 2020 | 1034 |
| 2 | Recent trends in biocatalysis Hit paper breakdown → | 2021 | 272 |
| 3 | 2016 | 149 | |
| 4 | 2017 | 95 | |
| 5 | 2020 | 90 | |
| 6 | 2020 | 85 | |
| 7 | 2013 | 83 | |
| 8 | 2017 | 74 | |
| 9 | 2016 | 71 | |
| 10 | 2019 | 70 | |
| 11 | 2013 | 66 | |
| 12 | 2017 | 62 | |
| 13 | 2014 | 61 | |
| 14 | 2018 | 58 | |
| 15 | 2020 | 54 | |
| 16 | 2014 | 45 | |
| 17 | 2021 | 41 | |
| 18 | 2018 | 38 | |
| 19 | 2019 | 36 | |
| 20 | 2017 | 36 |
About Shuke Wu
Shuke Wu is a scholar working on Pharmacology, Molecular Biology, Biochemistry, Biomedical Engineering and Organic Chemistry, having authored 46 papers that have together received 2.9k indexed citations. Recurring topics across this work include Enzyme Catalysis and Immobilization (33 papers), Microbial Metabolic Engineering and Bioproduction (25 papers), Biofuel production and bioconversion (9 papers), Pharmacogenetics and Drug Metabolism (6 papers), Chemical Synthesis and Analysis (5 papers), Catalysis for Biomass Conversion (4 papers), Steroid Chemistry and Biochemistry (4 papers) and Carbohydrate Chemistry and Synthesis (4 papers). The work is most often cited by research in Molecular Biology (2.3k citations), Organic Chemistry (733 citations), Inorganic Chemistry (351 citations), Biochemistry (179 citations) and Pharmacology (191 citations). Shuke Wu has collaborated with scholars based in Singapore, Germany and China. Frequent co-authors include Uwe T. Bornscheuer, Zhi Li, Radka Šnajdrová, Kai Baldenius, Jeffrey C. Moore, Yi Zhou, Christoffel P. S. Badenhorst, Thomas Bayer, Aitao Li and Matthias Höhne. Their work appears in journals such as Angewandte Chemie International Edition, Nature Communications, ACS Catalysis, Chemical Communications and ChemCatChem.
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.