Fedor Grab

The paper introduces SOCAM, a supervised cell annotation method that enforces ontological consistency and improves performance using a probability propagation strategy and logistic regression model.

This paper introduces a service for automated cell type annotation in scRNA-seq data using reverse search against a curated database, providing both fine-grained and coarse annotations without relying on predefined markers.

TissueMosaic performs cross-sample differential analysis of spatial transcriptomics data using self-supervised representation learning to improve detection of genes associated with tissue structure changes.