Kyle Swanson

22 papers receiving 3.8k citations

Kyle Swanson's Hit Papers

The Virtual Lab of AI agents designs new SARS-CoV-2 nanobodies 2025 · 34 citations
340+2+4Years since publication4008001.2k

Peers

Kyle Swanson
Comparison fields: 5 of 179
  • Computational Theory and Mathematics 1.6k
  • Health Informatics 124
  • Applied Microbiology and Biotechnology 76
  • Molecular Medicine 195
  • Biophysics 160
Replace Wengong Jin with:
Wengong Jin United States
Kevin Yang United States
Anush Chiappino-Pepe United States
Emma J. Chory United States
Andrés Cubillos-Ruiz United States
Ian W. Andrews United States
Zohar Bloom‐Ackermann Israel
Lindsey A. Carfrae Canada
Shawn French Canada
Victoria M. Tran United States
Kyle Swanson relative to Wengong Jin United States Wengong Jin's profile →
Citations per field
00.5×1.5×
Wengong Jin · 1×
Citations per year

Countries citing papers authored by Kyle Swanson

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Kyle Swanson Line = papers co-authored together Kyle Swanson links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A Deep Learning Approach to Antibiotic Discovery
Hit paper breakdown →
20201468
2
Analyzing Learned Molecular Representations for Property Prediction
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20191186
3
From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment
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2023337
4
Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii
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2023210
5 2018203
6
ADMET-AI: a machine learning ADMET platform for evaluation of large-scale chemical libraries
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2024130
7
Generative AI for designing and validating easily synthesizable and structurally novel antibiotics
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202497
8 202278
9 202445
10
The Virtual Lab of AI agents designs new SARS-CoV-2 nanobodies
Hit paper breakdown →
202534
11 202432
12 201927
13 202420
14 202316
15 202116
16 202412
17
Testing of Cryogenic Photomultiplier Tubes for the MicroBooNE Experiment
20165
18 20234
19 20204
20 20242

About Kyle Swanson

Kyle Swanson is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Artificial Intelligence and Biophysics, having authored 26 papers that have together received 3.9k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Cell Image Analysis Techniques (4 papers), Machine Learning in Materials Science (4 papers), Single-cell and spatial transcriptomics (3 papers), Cancer Genomics and Diagnostics (2 papers), Pluripotent Stem Cells Research (2 papers), Neurobiology of Language and Bilingualism (2 papers) and Biomedical Text Mining and Ontologies (2 papers). The work is most often cited by research in Computational Theory and Mathematics (1.6k citations), Health Informatics (124 citations), Applied Microbiology and Biotechnology (76 citations), Molecular Medicine (195 citations) and Biophysics (160 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, Angel Guzmán-Pérez, Brian Kelley and Philipp Eiden. Their work appears in journals such as Nature Methods, Journal of Chemical Information and Modeling, Cell, Frontiers in Human Neuroscience and The Annual Review of Pharmacology and Toxicology.

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.

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