Author

Christina Demuth

Aarhus University HospitalORCID 0000-0003-0237-9758Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 1 Approach:deep learning· 1 Organism:human· 1 Research Focus:variant calling· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Amanda FrydendahliD· 1 shared Claus L. AnderseniD· 1 shared Iben LyskjæriD· 1 shared Jakob Skou PederseniD· 1 shared Jesper NorsiD· 1 shared Kåre Andersson GotschalckiD· 1 shared Lene Hjerrild IverseniD· 1 shared Mads Heilskov RasmusseniD· 1 shared

Activity by Year

2022-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Amanda FrydendahlORCID

Mutual co-authors in cluster

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1 paper

Recent·Most cited

DREAMS: Deep Read-level Error Model for Sequencing data applied to low-frequency variant calling and circulating tumor DNA detection

Mikkel Hovden Christensen, Simon Opstrup Drue, Mads Heilskov Rasmussen, Amanda Frydendahl, Iben Lyskjær, Christina Demuth, Jesper Nors, Kåre Andersson Gotschalck, Lene Hjerrild Iversen, Claus L. Andersen, Jakob Skou Pedersen

DREAMS improves variant calling and circulating tumor DNA detection by modeling sequencing errors at the read level using deep learning.

bioRxiv · Sep 27, 2022 · PreprintBioinformatics