Author

Julianne V. Kus

University of TorontoORCID 0000-0001-6033-7244Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:C. elegans· 1 Research Focus:GWAS / association mapping· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Adarsh Jay· 1 shared Alicia PageauiD· 1 shared Amrita BharatiD· 1 shared Anna FijarczykiD· 1 shared Camille BédardiD· 1 shared Carla BautistaiD· 1 shared Christian R. LandryiD· 1 shared Domenica G. De LucaiD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperMicrobiology

Adarsh Jay

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1 paper

Recent·Most cited

MicrobiologybioRxivPreprintOct 29, 2026

Population genomics of Candida albicans reveals genetic footprints that allow the prediction of antifungal resistance

Adarsh Jay, Camille Bédard, Alicia Pageau…·Christian R. Landry

This study uses population genomics and machine learning to identify genetic markers predictive of antifungal resistance in Candida albicans, highlighting the need for expanded resistance catalogues.

DOI 10.64898/2026.10.28.762049

C. eleganswhole-genome sequencing

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