Author

Anja Seidel

Robert Koch InstituteORCID 0000-0001-6856-728XUnclaimed 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:bacteria (other)· 1 Assay:DNA methylation· 1 Organism:human· 1 Research Focus:variant calling· 1 Research Focus:variant effect prediction· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Bernhard Y. RenardiD· 2 shared Jakub M. BartoszewicziD· 2 shared Robert RentzschiD· 1 shared

Activity by Year

2019-2021 · peak 1/yr

Co-Author Collaboration Network

3 top collaborators · 3 mutual co-author links

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2 shared papersBioinformatics

Bernhard Y. RenardORCID

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2 papers

Recent·Most cited

BioinformaticsNAR Genomics and BioinformaticsPeer-reviewedFeb 1, 2021

Interpretable detection of novel human viruses from genome sequencing data

Jakub M. Bartoszewicz, Anja Seidel, Bernhard Y. Renard

This paper develops a deep learning method to detect novel human viruses from genome sequencing data, achieving lower error rates than existing methods and providing interpretability tools for analysis.

65 citationstop 4%

humanwhole-genome sequencing

𝕏 PostBluesky

BioinformaticsBioinformaticsPeer-reviewedJul 11, 2019

DeePaC: Predicting pathogenic potential of novel DNA with reverse-complement neural networks

Jakub M. Bartoszewicz, Anja Seidel, Robert Rentzsch, Bernhard Y. Renard

DeePaC predicts pathogenic potential of novel DNA sequences using reverse-complement neural networks, reducing error rates compared to existing methods.

66 citations

bacteria (other)DNA methylation

𝕏 PostBluesky