Author

Aidan R. O’Brien

Australian National UniversityORCID 0000-0003-3525-8469Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 3 Genetics· 1

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 3 Research Focus:benchmarking· 2 Organism:mouse· 2 Assay:CRISPR screen· 1 Research Focus:software / tool· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Denis C. BaueriD· 3 shared Gaétan BurgioiD· 2 shared Amy Gonzales· 1 shared Andrew S. I. LoudoniD· 1 shared Andrew W. TraffordiD· 1 shared Ane Miren SalvadoriD· 1 shared Anne N. HarringtoniD· 1 shared Antony D. AdamsoniD· 1 shared

Activity by Year

2019-2023 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 23 mutual co-author links

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3 shared papersBioinformatics

Denis C. BauerORCID

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4 papers

Recent·Most cited

BioinformaticsPLoS ONEPeer-reviewedOct 17, 2023

Predicting CRISPR-Cas12a guide efficiency for targeting using Machine Learning

Aidan R. O’Brien, Denis C. Bauer, Gaétan Burgio

The paper uses machine learning to improve Cas12a guide RNA efficiency prediction by analyzing nucleotide bias and mismatches relative to the PAM site.

13 citations

machine learning (classical)variant effect prediction

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GeneticsGenome biologyPeer-reviewedAug 25, 2019

Re-Evaluating One-step Generation of Mice Carrying Conditional Alleles by CRISPR-Cas9-Mediated Genome Editing Technology

Channabasavaiah B. Gurumurthy, Aidan R. O’Brien, Rolen M. Quadros…·Atsushi Yoshiki

The paper re-evaluates the efficiency of a CRISPR-Cas9 method for generating conditional knockout alleles in mice, finding very low success rates and high rates of undesired alleles.

102 citationstop 3%

mousestatistical model

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BioinformaticsbioRxivPreprintJul 15, 2019

VariantSpark, A Random Forest Machine Learning Implementation for Ultra High Dimensional Data

Arash Bayat, Piotr Szul, Aidan R. O’Brien…·Denis C. Bauer

This paper introduces CursedForest, a Random Forest implementation that scales to millions of features and outperforms existing methods in speed.

2 citations

machine learning (classical)benchmarking

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BioinformaticsScientific ReportsPeer-reviewedFeb 26, 2019

Unlocking HDR-mediated Nucleotide Editing by identifying high-efficiency target sites using machine learning

Aidan R. O’Brien, Laurence O. W. Wilson, Gaétan Burgio, Denis C. Bauer

The paper identifies high-efficiency HDR target sites using machine learning and develops a tool to design optimal nucleotide editing strategies.

48 citations

mouseCRISPR screen

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