Anh‐Tien Ton
- Computational Theory and Mathematics top 0.5%
- Molecular Biology
- Infectious Diseases top 5%
- Materials Chemistry
- Organic Chemistry
- Co-authors
- Artem CherkasovFuqiang BanFrancesco GentileMichael HsingMichael FernándezMartin GleaveUlf NorinderAbraham C. Stern
- Topics
- Computational Drug Discovery Methods (7 papers)vaccines and immunoinformatics approaches (3 papers)Protein Structure and Dynamics (3 papers)
- Partner nations
- CanadaUnited KingdomUnited States
In The Last Decade
Anh‐Tien Ton
13 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Computational Theory and Mathematics 802
- Molecular Biology 614
- Infectious Diseases 386
- Materials Chemistry 210
- Organic Chemistry 146
Countries citing papers authored by Anh‐Tien Ton
This map shows the geographic impact of Anh‐Tien Ton'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 Anh‐Tien Ton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anh‐Tien Ton more than expected).
Fields of papers citing papers by Anh‐Tien Ton
This network shows the impact of papers produced by Anh‐Tien Ton. 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 Anh‐Tien Ton. The network helps show where Anh‐Tien Ton may publish in the future.
Co-authorship network of co-authors of Anh‐Tien Ton
This figure shows the co-authorship network connecting the top 25 collaborators of Anh‐Tien Ton. A scholar is included among the top collaborators of Anh‐Tien Ton based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Anh‐Tien Ton. Anh‐Tien Ton is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 54 | |
| 3 | Artificial intelligence–enabled virtual screening of ultra-large chemical libraries with deep dockingbreakdown → | 218 |
| 4 | 32 | |
| 5 | 10 | |
| 6 | 30 | |
| 7 | 46 | |
| 8 | Deep Docking: A Deep Learning Platform for Augmentation of Structure Based Drug Discoverybreakdown → | 259 |
| 9 | 154 | |
| 10 | Rapid Identification of Potential Inhibitors of SARS‐CoV‐2 Main Protease by Deep Docking of 1.3 Billion Compoundsbreakdown → | 382 |
| 11 | 20 | |
| 12 | 11 | |
| 13 | 13 |
About Anh‐Tien Ton
Anh‐Tien Ton is a scholar working on Computational Theory and Mathematics, Infectious Diseases and Molecular Biology, having authored 13 papers that have together received 1.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), vaccines and immunoinformatics approaches (3 papers) and Protein Structure and Dynamics (3 papers). The work is most often cited by research in Computational Theory and Mathematics (802 citations), Infectious Diseases (386 citations) and Health Informatics (18 citations). Anh‐Tien Ton has collaborated with scholars based in Canada, United Kingdom and United States. Frequent co-authors include Artem Cherkasov, Fuqiang Ban, Francesco Gentile, Michael Hsing, Michael Fernández, Martin Gleave, Ulf Norinder, Abraham C. Stern, N.C.J. Strynadka and L.J. Worrall. Their work appears in journals such as Journal of Biological Chemistry, Nature Communications and Annals of Neurology.
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.