Author

Alexandra Danyi

University Medical Center UtrechtORCID 0000-0002-1857-0816Unclaimed 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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Research Focus:cell type annotation· 2 Organism:human· 2 Assay:whole-genome sequencing· 2 Approach:deep learning· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Jeroen de RidderiD· 2 shared Carla van Herpen· 1 shared Edwin Cuppen· 1 shared Gad Getz· 1 shared Gurnit Atwal· 1 shared ICGC/TCGA Pan-cancer Analysis of Whole Genomes Net· 1 shared Lincoln D. Stein· 1 shared Martijn P Lolkema· 1 shared

Activity by Year

2019-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersBioinformatics

Jeroen de RidderORCID

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2 papers

Recent·Most cited

BioinformaticsLifePeer-reviewedDec 21, 2021

Cancer type classification in liquid biopsies based on sparse mutational profiles enabled through data augmentation and integration

Alexandra Danyi, Myrthe Jager, Jeroen de Ridder

This paper develops a machine learning method to classify cancer cell of origin from sparse liquid biopsy data by using data augmentation and integration of multiple genomic features.

10 citations

humanwhole-genome sequencing

𝕏 PostBluesky

Cancer BiologybioRxivPreprintJan 22, 2019

A deep learning system can accurately classify primary and metastatic cancers based on patterns of passenger mutations

Wei Jiao, Gurnit Atwal, Paz Polak…·ICGC/TCGA Pan-cancer Analysis of Whole Genomes Net

This paper develops a deep learning classifier using whole genome sequencing data to distinguish cancer types and identify metastatic origins.

DOI 10.1101/214494

humanwhole-genome sequencing

𝕏 PostBluesky