Lars Feuerbach

The paper identifies genomic and transcriptomic features of telomere maintenance mechanisms in complex karyotype sarcomas, linking ALT status to therapeutic vulnerabilities.

This study uses Nanopore whole-genome sequencing to show conserved chromosome-specific telomere length patterns across tissues and populations, revealing coordinated regulation and potential disease risk factors.

The paper evaluates and optimizes sequence-based gene regulatory deep learning models using a DREAM Challenge dataset, showing improvements through architectural and training strategy refinements.

The paper introduces REMIND-Cancer Pipeline and pSNV Hunter to identify and prioritize functional promoter SNVs, including lowly recurrent and singleton mutations, using multi-omics data from the PCAWG dataset.

This paper develops a computational framework to quantify telomere content and composition from scATAC-seq data, revealing patient-specific telomere maintenance patterns in cancer and immune cells.

The paper identifies previously overlooked activating promoter mutations in cancer using a computational workflow applied to the PCAWG dataset, validating several candidates through luciferase assays.

The paper analyzes whole-genome sequencing data from cancer samples to identify genomic footprints of telomere maintenance mechanisms, finding specific telomere variant repeat patterns associated with ATRX/DAXX mutations.

The paper introduces the Cancer LncRNA Census (CLC), a curated resource of lncRNAs with causative roles in cancer, and shows their genomic and evolutionary features.

The paper examines how somatic structural variations affect TAD boundaries and gene regulation in human cancers using whole genome sequencing data.

This study analyzes chromothripsis in 2,658 cancers using whole-genome sequencing, finding it prevalent across multiple cancer types with complex structural alterations.

ActivePathways integrates multivariate omics data to identify enriched pathways, revealing cancer driver genes and prognostic pathways in breast cancer.

The paper identifies and characterizes coding and non-coding driver mutations across 2,500 cancer genomes, revealing new candidates and questioning previous findings.

TelomereHunter estimates and characterizes telomere content from whole genome sequencing data in cancer studies.

This study compares whole genome sequencing pipelines across five centers using a uniform tumor-normal sample pair, identifying factors affecting output consistency.