Michael Hsing
Impact in
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- Computational Drug Discovery Methods
- Infectious Diseases top 5%
- SARS-CoV-2 and COVID-19 Research
Papers in
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- Bioinformatics and Genomic Networks 5
- Ubiquitin and proteasome pathways 3
- Protein Structure and Dynamics 3
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- Prostate Cancer Treatment and Research 9
- Co-authors
- Artem Cherkasov (28 shared papers)Fuqiang Ban (9 shared papers)Anh‐Tien Ton (3 shared papers)Francesco Gentile (2 shared papers)Sek Won Kong (5 shared papers)Paul S. Rennie (13 shared papers)Martin Gleave (3 shared papers)Ulf Norinder (1 shared paper)
- Journals
- BMC Bioinformatics (4 papers)Bioinformatics (3 papers)Journal of Biological Chemistry (3 papers)Cancer Research (2 papers)Drug Discovery Today (1 paper)
- Partner nations
- CanadaUnited StatesUnited Kingdom
In The Last Decade
Michael Hsing
38 papers receiving 1.8k citations
Michael Hsing's Hit Papers
Peers
Comparison fields: 5 of 129
- Computational Theory and Mathematics 629
- Infectious Diseases 265
- Molecular Biology 954
- Genetics 255
- Cancer Research 119
Countries citing papers authored by Michael Hsing
This map shows the geographic impact of Michael Hsing'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 Michael Hsing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Hsing more than expected).
Fields of papers citing papers by Michael Hsing
This network shows the impact of papers produced by Michael Hsing. 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 Michael Hsing. The network helps show where Michael Hsing may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Hsing, 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 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Rapid Identification of Potential Inhibitors of SARS‐CoV‐2 Main Protease by Deep Docking of 1.3 Billion Compounds Hit paper breakdown → | 2020 | 402 |
| 2 | Deep Docking: A Deep Learning Platform for Augmentation of Structure Based Drug Discovery Hit paper breakdown → | 2020 | 293 |
| 3 | 2011 | 173 | |
| 4 | 2014 | 110 | |
| 5 | 2018 | 98 | |
| 6 | 2012 | 90 | |
| 7 | 2013 | 78 | |
| 8 | 2014 | 59 | |
| 9 | 2019 | 57 | |
| 10 | 2008 | 53 | |
| 11 | 2003 | 49 | |
| 12 | 2003 | 45 | |
| 13 | 2010 | 39 | |
| 14 | 2021 | 32 | |
| 15 | 2007 | 31 | |
| 16 | 2014 | 29 | |
| 17 | 2009 | 27 | |
| 18 | 2008 | 21 | |
| 19 | 2019 | 20 | |
| 20 | 2014 | 18 |
About Michael Hsing
Michael Hsing is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Computational Theory and Mathematics, Genetics and Radiology, Nuclear Medicine and Imaging, having authored 38 papers that have together received 1.8k indexed citations. Recurring topics across this work include Prostate Cancer Treatment and Research (9 papers), Computational Drug Discovery Methods (6 papers), Bioinformatics and Genomic Networks (5 papers), Ubiquitin and proteasome pathways (3 papers), Protein Structure and Dynamics (3 papers), Genomics and Rare Diseases (3 papers), Estrogen and related hormone effects (3 papers) and GaN-based semiconductor devices and materials (3 papers). The work is most often cited by research in Computational Theory and Mathematics (629 citations), Infectious Diseases (265 citations), Molecular Biology (954 citations), Genetics (255 citations) and Cancer Research (119 citations). Michael Hsing has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Artem Cherkasov, Fuqiang Ban, Anh‐Tien Ton, Francesco Gentile, Sek Won Kong, Paul S. Rennie, Martin Gleave, Ulf Norinder, Isaac S. Kohane and Eric Leblanc. Their work appears in journals such as BMC Bioinformatics, Bioinformatics, Journal of Biological Chemistry, Cancer Research and Drug Discovery Today.
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.