Dominik J. Otto

This study identifies molecular and architectural changes in normal-adjacent field tissue in HNSCC that disrupt epithelial differentiation and may promote cancer development.

AnnZarro enables interactive exploration of cell-by-cell and gene-by-gene relationships in single-cell data through a browser-based viewer linked to AnnData objects.

Echo identifies desynchronized cell states and their drivers from paired single-cell RNA and ATAC data, revealing structured desynchronization in human fetal retina and hematopoiesis.

Kompot enables cluster-free differential expression analysis in single-cell data, identifying phenotypic shifts and transcriptional changes across conditions.

This study shows KMT2A oncoproteins drive lineage-switching and epigenetic resistance in leukemia by dynamically binding chromatin and persisting as ENL-marked lesions despite therapy.

The paper evaluates deconvolution methods for inferring immune infiltration from bulk gene expression using a DREAM Challenge, finding that some community-contributed methods, especially deep learning-based ones, perform well.

The paper introduces Mellon, a method to estimate cell-state densities in single-cell data, revealing high-density regions for major cell types and low-density regions for rare transitory states.

The paper describes a modified CUT&Tag protocol that profiles both active and repressive regulatory elements in single cells using computational signal deconvolution.