Thomas Beder

The paper introduces ALLCatchR2, a machine learning classifier that identifies 20 T-ALL subtypes across multiple cohorts and age groups with high accuracy.

IntegrateALL is an RNA-seq pipeline that integrates expression-based subtyping, gene fusion detection, and virtual karyotyping to classify B-ALL with high accuracy.

This study identifies how developmental maturity and fusion partner influence treatment response in KMT2A-rearranged B-ALL across all ages.

This study presents the first comprehensive mutational and transcriptional analysis of B-cell precursor lymphoblastic lymphoma (BCP-LBL), revealing molecular similarities to BCP-ALL but with distinct mutation patterns in epigenetic modifiers.

The paper uses machine learning to predict essential genes across eukaryotes, achieving high accuracy and validating predictions in Tribolium castaneum.