Author

KLARA L. VERBYLA

Commonwealth Scientific and Industrial Research OrganisationORCID 0000-0001-8876-4301Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

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Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Hawlader Abdullah Al-MamuniD· 1 shared Robert A. DunneiD· 1 shared Ross L. TellamiD· 1 shared

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2022-2022 · peak 1/yr

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3 top collaborators · 3 mutual co-author links

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1 shared paperBioinformatics

Hawlader Abdullah Al-MamunORCID

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1 paper

Recent·Most cited

BioinformaticsbioRxivPreprintApr 26, 2022

Detecting epistatic interactions in genomic data using Random Forests

Hawlader Abdullah Al-Mamun, Robert A. Dunne, Ross L. Tellam, KLARA L. VERBYLA

This paper introduces a computationally efficient Random Forests method to detect epistatic interactions in genomic data and validates it on simulated and real datasets.

5 citations

whole-genome sequencingmachine learning (classical)

𝕏 PostBluesky