Kyle Swanson
Impact in
- Computational Theory and Mathematics top 0.2%
- Computational Drug Discovery Methods
- Health Informatics top 1%
Papers in
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- Single-cell and spatial transcriptomics 3
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- Computational Drug Discovery Methods 6
- Co-authors
- Regina Barzilay (6 shared papers)Wengong Jin (5 shared papers)Tommi Jaakkola (5 shared papers)Kevin Yang (4 shared papers)James Zou (9 shared papers)Anush Chiappino-Pepe (2 shared papers)James J. Collins (2 shared papers)Miriam Mathea (2 shared papers)
- Journals
- Nature Methods (2 papers)Cell (2 papers)Journal of Chemical Information and Modeling (2 papers)Proceedings of the Royal Society B Biological Sciences (1 paper)Bioinformatics (1 paper)
- Partner nations
- United StatesCanadaGermany
In The Last Decade
Kyle Swanson
21 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 178
- Computational Theory and Mathematics 1.5k
- Health Informatics 122
- Molecular Medicine 187
- Applied Microbiology and Biotechnology 72
- Biophysics 143
Countries citing papers authored by Kyle Swanson
This map shows the geographic impact of Kyle Swanson'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 Kyle Swanson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyle Swanson more than expected).
Fields of papers citing papers by Kyle Swanson
This network shows the impact of papers produced by Kyle Swanson. 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 Kyle Swanson. The network helps show where Kyle Swanson may publish in the future.
Co-authors
The 25 scholars most cited alongside Kyle Swanson, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A Deep Learning Approach to Antibiotic Discovery Hit paper breakdown → | 2020 | 1298 |
| 2 | Analyzing Learned Molecular Representations for Property Prediction Hit paper breakdown → | 2019 | 1081 |
| 3 | From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment Hit paper breakdown → | 2023 | 282 |
| 4 | 2018 | 188 | |
| 5 | Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii Hit paper breakdown → | 2023 | 183 |
| 6 | ADMET-AI: a machine learning ADMET platform for evaluation of large-scale chemical libraries Hit paper breakdown → | 2024 | 88 |
| 7 | Generative AI for designing and validating easily synthesizable and structurally novel antibiotics Hit paper breakdown → | 2024 | 83 |
| 8 | 2022 | 67 | |
| 9 | 2024 | 32 | |
| 10 | 2019 | 25 | |
| 11 | 2024 | 21 | |
| 12 | The Virtual Lab of AI agents designs new SARS-CoV-2 nanobodies Hit paper breakdown → | 2025 | 18 |
| 13 | 2023 | 12 | |
| 14 | 2024 | 12 | |
| 15 | 2021 | 12 | |
| 16 | 2024 | 8 | |
| 17 | Testing of Cryogenic Photomultiplier Tubes for the MicroBooNE Experiment | 2016 | 5 |
| 18 | 2020 | 4 | |
| 19 | 2023 | 3 | |
| 20 | 2024 | 1 |
About Kyle Swanson
Kyle Swanson is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Artificial Intelligence and Biophysics, having authored 22 papers that have together received 3.4k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Machine Learning in Materials Science (5 papers), Cell Image Analysis Techniques (4 papers), Single-cell and spatial transcriptomics (3 papers), AI in cancer detection (2 papers), Parasite Biology and Host Interactions (2 papers), 3D Printing in Biomedical Research (2 papers) and Cancer Genomics and Diagnostics (2 papers). The work is most often cited by research in Computational Theory and Mathematics (1.5k citations), Health Informatics (122 citations), Molecular Medicine (187 citations), Applied Microbiology and Biotechnology (72 citations) and Biophysics (143 citations). Kyle Swanson has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Regina Barzilay, Wengong Jin, Tommi Jaakkola, Kevin Yang, James Zou, Anush Chiappino-Pepe, James J. Collins, Miriam Mathea, Connor W. Coley and Klavs F. Jensen. Their work appears in journals such as Nature Methods, Cell, Journal of Chemical Information and Modeling, Proceedings of the Royal Society B Biological Sciences and Bioinformatics.
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.