Author

Mads Kærn

University of OttawaORCID 0000-0002-9371-666XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Assay:imaging· 1 Approach:statistical model· 1

Frequent Co-Authors

Danny SalemiD· 1 shared Hilary Phenix· 1 shared Jonathan M. LeeiD· 1 shared Miroslava Čuperlović‐CulfiD· 1 shared Nasser Bashkeel· 1 shared Pengcheng XiiD· 1 shared Theodore J. PerkinsiD· 1 shared Yifeng LiiD· 1 shared

Activity by Year

2019-2021 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 13 mutual co-author links

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1 shared paperBioinformatics

Danny SalemORCID

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2 papers

Recent·Most cited

YeastNet: Deep Learning Enabled Accurate Segmentation of Budding Yeast Cells in Bright-field Microscopy

Danny Salem, Yifeng Li, Pengcheng Xi, Hilary Phenix, Miroslava Čuperlović‐Culf, Mads Kærn

YeastNet improves yeast cell segmentation in bright-field microscopy using a U-Net model, outperforming existing tools and providing a Python package for automated analysis.

Applied Sciences · Mar 17, 2021Peer-reviewedBioinformatics

Human Gene Expression Variability and its Dependence on Methylation and Aging

Nasser Bashkeel, Theodore J. Perkins, Mads Kærn, Jonathan M. Lee

The paper classifies human genes by expression variability in breast and brain tissues, finding that high variability is unimodal and influenced by age and methylation.

BMC Genomics · Dec 1, 2019Peer-reviewedBioinformatics