Author

James O’Connor

Virginia Energy

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioengineering· 1 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 1 Assay:GWAS summary statistics· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:polygenic risk· 1 Research Focus:software / tool· 1 Approach:statistical model· 1

Frequent Co-Authors

Steven L. Armentrout· 2 shared Carlos CruchagaiD· 1 shared Curt R. Larock· 1 shared Dabrien Murphy· 1 shared Douglas Blair· 1 shared Ellen McRae GreytakiD· 1 shared Janet Cady· 1 shared Paul Sorensen· 1 shared

Activity by Year

2023-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersBioengineering

Steven L. Armentrout

Mutual co-authors in cluster

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2 papers

Recent·Most cited

inSequio: A Programmable 3D CAD Application for Designing DNA Nanostructures

Curt R. Larock, Paul Sorensen, Douglas Blair, Dabrien Murphy, James O’Connor, Steven L. Armentrout

inSequio is a programmable 3D CAD tool for DNA nanostructure design that combines manual and programmatic editing, enhancing precision, scalability, and efficiency in DNA nanotechnology.

bioRxiv · Mar 27, 2024 · PreprintBioengineering

Epistatic Features and Machine Learning Improve Alzheimer's Risk Prediction Over Polygenic Risk Scores

Stephen Hermes, Janet Cady, Steven L. Armentrout, James O’Connor, Sarah E. Carlson, Carlos Cruchaga, Thomas S. Wingo, Ellen McRae Greytak, The Alzheimer’s Disease Neuroimaging Initiative

This study develops a paragenic risk score that improves Alzheimer's disease risk prediction by incorporating epistatic interactions and machine learning, outperforming traditional polygenic risk scores.

medRxiv · Feb 10, 2023 · PreprintGenetic & Genomic Medicine