Ryan Byrne
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
-
- Computational Drug Discovery Methods
Papers in
-
- Metabolomics and Mass Spectrometry Studies 2
- Peroxisome Proliferator-Activated Receptors 1
- Plant biochemistry and biosynthesis 1
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- Computational Drug Discovery Methods 4
- Co-authors
- Gisbert Schneider (6 shared papers)Xin Yang (1 shared paper)Shengyong Yang (1 shared paper)Yifei Wang (1 shared paper)Daniel Merk (1 shared paper)Francesca Grisoni (1 shared paper)Inderjeet Singh (1 shared paper)Lukas Friedrich (1 shared paper)
- Journals
- Neuro-Oncology (1 paper)ChemMedChem (1 paper)Journal of Chemical Information and Modeling (1 paper)Chemical Reviews (1 paper)Scientific Reports (1 paper)
- Partner nations
- SwitzerlandGermanyUnited States
In The Last Decade
Ryan Byrne
7 papers receiving 708 citations
Ryan Byrne's Hit Papers
Peers
Comparison fields: 5 of 124
- Health Informatics 32
- Computational Theory and Mathematics 385
- Biophysics 37
- Molecular Biology 322
- Materials Chemistry 191
Countries citing papers authored by Ryan Byrne
This map shows the geographic impact of Ryan Byrne'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 Ryan Byrne with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryan Byrne more than expected).
Fields of papers citing papers by Ryan Byrne
This network shows the impact of papers produced by Ryan Byrne. 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 Ryan Byrne. The network helps show where Ryan Byrne may publish in the future.
Co-authors
The 25 scholars most cited alongside Ryan Byrne, 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 | Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery Hit paper breakdown → | 2019 | 653 |
| 2 | 2018 | 32 | |
| 3 | 2018 | 23 | |
| 4 | 2020 | 5 | |
| 5 | 2021 | 3 | |
| 6 | 2023 | 2 | |
| 7 | 2019 | 1 | |
| 8 | 2024 | 0 |
About Ryan Byrne
Ryan Byrne is a scholar working on Molecular Biology, Computational Theory and Mathematics, Pharmacology, Infectious Diseases and Control and Systems Engineering, having authored 8 papers that have together received 719 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (4 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Microbial Natural Products and Biosynthesis (2 papers), Peroxisome Proliferator-Activated Receptors (1 paper), Trypanosoma species research and implications (1 paper), Plant biochemistry and biosynthesis (1 paper), Systems Engineering Methodologies and Applications (1 paper) and Ziziphus Jujuba Studies and Applications (1 paper). The work is most often cited by research in Health Informatics (32 citations), Computational Theory and Mathematics (385 citations), Biophysics (37 citations), Molecular Biology (322 citations) and Materials Chemistry (191 citations). Ryan Byrne has collaborated with scholars based in Switzerland, Germany and United States. Frequent co-authors include Gisbert Schneider, Xin Yang, Shengyong Yang, Yifei Wang, Daniel Merk, Francesca Grisoni, Inderjeet Singh, Lukas Friedrich, Christoph Bauer and Ursula Storch. Their work appears in journals such as Neuro-Oncology, ChemMedChem, Journal of Chemical Information and Modeling, Chemical Reviews and Scientific Reports.
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.