Author

Dalton T. Ham

Western University

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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Bioinformatics· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 2 Organism:bacteria (other)· 1 Research Focus:benchmarking· 1 Assay:CRISPR screen· 1 Research Focus:gene regulatory network inference· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

David R. EdgelliD· 2 shared Gregory Brian GlooriD· 2 shared Tyler S. BrowneiD· 2 shared Claire Q. Zhang· 1 shared Gary W. FooiD· 1 shared Pooja N. Banglorewala· 1 shared Richard K. Michael· 1 shared Tyler L. Wilson· 1 shared

Activity by Year

2023-2025 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 22 mutual co-author links

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2 shared papersMicrobiology

David R. EdgellORCID

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2 papers

Recent·Most cited

MicrobiologybioRxivPreprintAug 13, 2025

PAM adenine methylation and flanking sequence regulate SaCas9 activity in bacteria

Dalton T. Ham, Tyler S. Browne, Claire Q. Zhang…·David R. Edgell

This study uses machine learning to predict SaCas9 activity in bacteria, revealing that PAM adenine methylation and flanking sequences significantly influence activity.

DOI 10.1101/2025.08.13.670096

bacteria (other)CRISPR screen

𝕏 PostBluesky

BioinformaticsNature CommunicationsPeer-reviewedSep 7, 2023

A generalizable Cas9/sgRNA prediction model using machine transfer learning with small high-quality datasets

Dalton T. Ham, Tyler S. Browne, Pooja N. Banglorewala…·David R. Edgell

The paper develops a transfer learning model, crisprHAL, to improve SpCas9/sgRNA activity prediction using small high-quality datasets.

31 citations

machine learning (classical)

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