Author

Christina Demuth

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

Biology Disciplines

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Bioinformatics· 1 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:human· 2 Research Focus:variant calling· 2 Research Focus:cell type annotation· 1 Assay:whole-exome sequencing· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Amanda FrydendahliD· 2 shared Claus Lindbjerg AnderseniD· 2 shared Jakob Skou PederseniD· 2 shared Mads Heilskov RasmusseniD· 2 shared Henrik Jørn DitzeliD· 1 shared Iben LyskjæriD· 1 shared Jesper NorsiD· 1 shared Kåre Andersson GotschalckiD· 1 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersCancer Biology

Amanda FrydendahlORCID

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2 papers

Recent·Most cited

Cancer BiologyInternational Journal of Molecular SciencesPeer-reviewedApr 11, 2024

Error-corrected deep targeted sequencing of circulating cell-free DNA from colorectal cancer patients for sensitive detection of circulating tumor DNA

Amanda Frydendahl, Mads Heilskov Rasmussen, Sarah Østrup Jensen…·Claus Lindbjerg Andersen

UMIseq detects circulating tumor DNA in colorectal cancer patients with high sensitivity and specificity, even at low allele frequencies.

25 citations

humanwhole-exome sequencing

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BioinformaticsbioRxivPreprintSep 27, 2022

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…·Jakob Skou Pedersen

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

DOI 10.1101/2022.09.27.509150

humanwhole-genome sequencing

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