Author

Philipp Rentzsch

Science for Life LaboratoryORCID 0000-0002-0413-7974Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 4 Approach:statistical model· 4 Assay:bulk RNA-seq· 3 Research Focus:differential expression· 2 Research Focus:gene regulatory network inference· 2 Assay:ChIP-seq· 1 Research Focus:variant effect prediction· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Tuuli LappalaineniD· 2 shared Aaron KollotzekiD· 1 shared Carl HerrmanniD· 1 shared Carolin AndreseniD· 1 shared Daniel Hüebschmann· 1 shared Jeongbin ParkiD· 1 shared Júlia DomingoiD· 1 shared Kaushik Ram GanapathyiD· 1 shared

Activity by Year

2017-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 12 mutual co-author links

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2 shared papersGenomics

Tuuli LappalainenORCID

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4 papers

Recent·Most cited

Recalibrating differential gene expression by genetic dosage variance prioritizes functionally relevant genes

Philipp Rentzsch, Aaron Kollotzek, Kaushik Ram Ganapathy, Pejman Mohammadi, Tuuli Lappalainen

This paper recalibrates differential gene expression by genetic dosage variance to prioritize functionally relevant genes, showing enrichment in metabolic and regulatory pathways.

Genome Research · Oct 1, 2025Peer-reviewedGenomics

varCADD: large sets of standing genetic variation enable genome-wide pathogenicity prediction

Lusiné Nazaretyan, Philipp Rentzsch, Martin Kircher

The paper introduces varCADD, a method using standing genetic variation to predict variant pathogenicity, showing improved accuracy over existing tools in certain genomic regions.

Genome Medicine · Aug 4, 2025Peer-reviewedBioinformatics

Specifying cellular context of transcription factor regulons for exploring context-specific gene regulation programs

Mariia Minaeva, Júlia Domingo, Philipp Rentzsch, Tuuli Lappalainen

The paper develops a method to define cell-specific transcription factor regulons and demonstrates their utility in analyzing transcriptional dysregulation in cancer.

NAR Genomics and Bioinformatics · Dec 20, 2024Peer-reviewedBioinformatics

Deciphering programs of transcriptional regulation by combined deconvolution of multiple omics layers

Daniel Hüebschmann, Nils Kurzawa, Sebastian Steinhauser, Philipp Rentzsch, Stephen Krämer, Carolin Andresen, Jeongbin Park, Roland Eils, Matthias Schlesner, Carl Herrmann

The paper introduces a method to disentangle multi-omics data and identifies regulatory mechanisms in human blood cells.

bioRxiv · Oct 8, 2017 · PreprintGenomics