Author

Sarah Østrup Jensen

Aarhus UniversityORCID 0000-0001-6044-3362Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:human· 2 Research Focus:variant calling· 2 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1 Assay:whole-exome sequencing· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Amanda FrydendahliD· 2 shared Claus Lindbjerg AnderseniD· 2 shared Mads Heilskov RasmusseniD· 2 shared Tenna Vesterman HenrikseniD· 2 shared Adam J. WidmaniD· 1 shared Aditya S. DeshpandeiD· 1 shared Alexandre Pellan ChengiD· 1 shared Andrew J. J. MungalliD· 1 shared

Activity by Year

2024-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersGenomics

Amanda FrydendahlORCID

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2 papers

Recent·Most cited

GenomicsNature MedicinePeer-reviewedJun 1, 2024

Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

Adam J. Widman, Minita J. Shah, Amanda Frydendahl…·Dan Avi Landau

This paper introduces MRD-EDGE, a machine learning platform for ultrasensitive ctDNA detection in plasma WGS, showing improved sensitivity and broader applicability for MRD monitoring.

138 citationstop 1%

humanwhole-genome sequencing

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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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