Hartmut Döhner

The paper develops a hierarchical classification framework combining epigenetic and genetic data with machine learning to improve diagnosis and risk stratification in hematologic malignancies.

This paper introduces Split-flow, a pipeline that uses concordance between demultiplexing methods to classify cell quality in multiplexed single-cell data, revealing structured quality gradients.

This paper shows menin inhibitors increase CLEC12A expression in AML, making it more responsive to CLEC12A-targeted CAR T cells, improving treatment outcomes.

Pyjacker detects enhancer hijacking in AML, identifying MNX1 activation via 7q deletion as a novel oncogenic mechanism.

The paper identifies del(5q) AML as an epigenetically distinct subgroup driven by KDM3B haploinsufficiency, linked to DNA hypermethylation and H3K9me1/2 dysregulation.