Author

Aidan M. Lewis

Colorado State UniversityORCID 0000-0002-3033-8446Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Organism:human· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Gregory P. SwansoniD· 1 shared Jared J. Luxton· 1 shared Lynn E. TayloriD· 1 shared Miles J. McKennaiD· 1 shared Sameer G. JhavariD· 1 shared Susan M. BaileyiD· 1 shared

Activity by Year

2021-2021 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 15 mutual co-author links

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1 shared paperBioinformatics

Gregory P. SwansonORCID

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1 paper

Recent·Most cited

Telomere length and chromosomal instability for predicting individual radiosensitivity and risk via machine learning

Jared J. Luxton, Miles J. McKenna, Aidan M. Lewis, Lynn E. Taylor, Sameer G. Jhavar, Gregory P. Swanson, Susan M. Bailey

The paper uses machine learning to predict individual radiosensitivity and risk based on telomere length and chromosomal instability data from prostate cancer patients undergoing radiotherapy.

Journal of Personalized Medicine · Mar 8, 2021Peer-reviewedBioinformatics