Author

Arash Bayat

Commonwealth Scientific and Industrial Research OrganisationORCID 0000-0002-8799-7776Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 3 Assay:GWAS summary statistics· 2 Approach:machine learning (classical)· 2 Research Focus:fine-mapping· 1 Research Focus:GWAS / association mapping· 1 Organism:human· 1 Approach:statistical model· 1

Frequent Co-Authors

Denis C. BaueriD· 3 shared Brendan HoskingiD· 2 shared Natalie A. TwineiD· 2 shared Piotr SzuliD· 2 shared Robert A. DunneiD· 2 shared Yatish JainiD· 2 shared Aidan R. O’BrieniD· 1 shared Cameron HoskingiD· 1 shared

Activity by Year

2019-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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3 shared papersBioinformatics

Denis C. BauerORCID

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3 papers

Recent·Most cited

Novel Alzheimer's disease genes and epistasis identified using machine learning GWAS platform

Mischa Lundberg, Letitia M.F. Sng, Piotr Szul, Robert A. Dunne, Arash Bayat, Samantha C. Burnham, Denis C. Bauer, Natalie A. Twine, the Alzheimer’s Disease Neuroimaging Initiative

This study identifies novel Alzheimer's disease genes and epistasis using machine learning GWAS tools, capturing more phenotypic variance and discovering new loci with epistatic interactions.

Scientific Reports · Oct 17, 2023Peer-reviewedGenetic & Genomic Medicine

BitEpi: A Fast and Accurate Exhaustive Higher-Order Epistasis Search

Arash Bayat, Brendan Hosking, Yatish Jain, Cameron Hosking, Milindi Kodikara, Daniel Reti, Natalie A. Twine, Denis C. Bauer

BitEpi efficiently identifies higher-order epistatic interactions among SNVs in genetic data, outperforming existing methods in speed and accuracy.

Scientific Reports · Aug 5, 2021Peer-reviewedBioinformatics

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

Arash Bayat, Piotr Szul, Aidan R. O’Brien, Robert A. Dunne, Oscar Junhong Luo, Yatish Jain, Brendan Hosking, Denis C. Bauer

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

bioRxiv · Jul 15, 2019 · PreprintBioinformatics