Frederik Otzen Bagger

Head of Bioinformatics

Rigshospitalet

Denmark

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About

Frederik Otzen Bagger is the Head of Bioinformatics at Rigshospitalet in Denmark. His research interests encompass bioinformatics in oncology, particularly focusing on genomic profiling, RNA expression signatures, and molecular subtyping of cancers. Recent publications include studies on pathophysiological insights into fever in children with cancer and the impact of genomic profiling on patient outcomes in personalized oncology.

Articles (16)

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2025

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2025

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2024

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2024

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2024

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2024

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2024

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2024

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2024

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2023

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2022

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2022

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2021

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2021

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2020

Collaborators (21)

Carolina Barra

Technical University of Denmark

DENMARK

Frederik Otzen Bagger

Research Interests

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About

Articles (16)

Fever in Children with Cancer: Pathophysiological Insights Using Blood Transcriptomics

Copenhagen Prospective Personalized Oncology (CoPPO)-impact of comprehensive genomic profiling in more than 2000 patients in a phase I setting.

Combining Homologous Recombination-Deficient Testing and Functional RAD51 Analysis Enhances the Prediction of Poly(ADP-Ribose) Polymerase Inhibitor Sensitivity

IMPROVE

BloodSpot 3.0

Host RNA Expression Signatures in Young Infants with Urinary Tract Infection: A Prospective Study

uPAR (PLAUR) Marks Two Intra-Tumoral Subtypes of Glioblastoma: Insights from Single-Cell RNA Sequencing

Building flexible and robust analysis frameworks for molecular subtyping of cancers

Glioblastoma cells increase expression of notch signaling and synaptic genes within infiltrated brain tissue.

Similar genetic profile in early and late stage urothelial tract cancer.

A Protocol for Low-Input RNA-Sequencing of Patients with Febrile Neutropenia Captures Relevant Immunological Information

H3K9 dimethylation safeguards cancer cells against activation of the interferon pathway

Benchmarking full-length transcript single cell mRNA sequencing protocols

A Comparison of Tools for Copy-Number Variation Detection in Germline Whole Exome and Whole Genome Sequencing Data

Interpretable Autoencoders Trained on Single Cell Sequencing Data Can Transfer Directly to Data from Unseen Tissues

Human erythroleukemia genetics and transcriptomes identify master transcription factors as functional disease drivers.

Collaborators (21)

Carolina Barra

Mikkel Bruhn Schuster

Sachin Pundhir

Eric Santoni-Rugiu

Dina Cortes

Erwin Marten Schoof

Virginie Deleuze-Marquès

Eric Soler

Bo Porse

Ying Ge

Kristian Helin

Connor Sweeney

Christina Bligaard Pedersen

Alessio Locallo

Sine Reker Hadrup

Arman Simonyan

Ibel Carri

Ulrikka Nygaard

Mansoor Mirza

Lars Rønn Olsen

Sebastien Malinge

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