Jack Hanson
Impact in
- Molecular Biology top 10%
- Protein Structure and Dynamics
- Machine Learning in Bioinformatics
- RNA and protein synthesis mechanisms
- Genomics and Phylogenetic Studies
- RNA modifications and cancer
- RNA Research and Splicing
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- Computational Drug Discovery Methods
Papers in
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- Protein Structure and Dynamics 10
- Machine Learning in Bioinformatics 6
- RNA and protein synthesis mechanisms 6
- Genomics and Phylogenetic Studies 2
- vaccines and immunoinformatics approaches 1
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- Enzyme Structure and Function 3
- Co-authors
- Kuldip K. Paliwal (14 shared papers)Yaoqi Zhou (13 shared papers)Yuedong Yang (8 shared papers)Thomas Litfin (6 shared papers)Jaswinder Singh (2 shared papers)Rhys Heffernan (3 shared papers)Jianzhao Gao (1 shared paper)Jihua Wang (1 shared paper)
- Journals
- Bioinformatics (4 papers)Journal of Chemical Information and Modeling (2 papers)Nature Communications (1 paper)Journal of Computational Biology (1 paper)Journal of Computational Chemistry (1 paper)
- Partner nations
- AustraliaChinaUnited States
In The Last Decade
Jack Hanson
15 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 104
- Molecular Biology 1.0k
- Computational Theory and Mathematics 125
- Materials Chemistry 232
- Structural Biology 3
- Cell Biology 30
Countries citing papers authored by Jack Hanson
This map shows the geographic impact of Jack Hanson'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 Jack Hanson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jack Hanson more than expected).
Fields of papers citing papers by Jack Hanson
This network shows the impact of papers produced by Jack Hanson. 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 Jack Hanson. The network helps show where Jack Hanson may publish in the future.
Co-authors
The 20 scholars most cited alongside Jack Hanson, 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 | 2019 | 238 | |
| 2 | 2016 | 216 | |
| 3 | 2016 | 173 | |
| 4 | 2018 | 142 | |
| 5 | 2018 | 139 | |
| 6 | 2019 | 107 | |
| 7 | 2018 | 58 | |
| 8 | 2018 | 54 | |
| 9 | 2019 | 48 | |
| 10 | 2019 | 38 | |
| 11 | 2019 | 15 | |
| 12 | 2018 | 13 | |
| 13 | 2019 | 9 | |
| 14 | 2018 | 5 | |
| 15 | 2025 | 1 |
About Jack Hanson
Jack Hanson is a scholar working on Molecular Biology, Materials Chemistry, Pharmaceutical Science, Signal Processing and Artificial Intelligence, having authored 15 papers that have together received 1.3k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (10 papers), Machine Learning in Bioinformatics (6 papers), RNA and protein synthesis mechanisms (6 papers), Enzyme Structure and Function (3 papers), Genomics and Phylogenetic Studies (2 papers), Speech Recognition and Synthesis (1 paper), Fluorine in Organic Chemistry (1 paper) and vaccines and immunoinformatics approaches (1 paper). The work is most often cited by research in Molecular Biology (1.0k citations), Computational Theory and Mathematics (125 citations), Materials Chemistry (232 citations), Structural Biology (3 citations) and Cell Biology (30 citations). Jack Hanson has collaborated with scholars based in Australia, China and United States. Frequent co-authors include Kuldip K. Paliwal, Yaoqi Zhou, Yuedong Yang, Thomas Litfin, Jaswinder Singh, Rhys Heffernan, Jianzhao Gao, Jihua Wang, Akila Katuwawala and Lukasz Kurgan. Their work appears in journals such as Bioinformatics, Journal of Chemical Information and Modeling, Nature Communications, Journal of Computational Biology and Journal of Computational Chemistry.
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.