Sebastian Birk

Multi-scale modeling of human tissues from spatial transcriptomics with TERRA

Spatial transcriptomics maps gene expression at cellular resolution, revealing how cells organize into multicellular niches. Yet computational analyses remain dataset-specific, without a transferable representation of tissue organization that generalizes across datasets, tasks and tissues or predicts how tissues behave...

G2T: Tissue Reconstruction from Gene Expression via Embedding-Distance Flow Matching

Single-cell RNA sequencing (scRNA-seq) profiles transcriptomes at high resolution but discards the spatial context of cells within a tissue—information that is essential for studying intercellular mechanisms and tissue architecture. Spatial transcriptomics (ST) retains coordinates but, depending on the assay, trades th...

Learning Discrete Cell and Niche Codes from Spatial Transcriptomics Using Dual Residual Vector Quantization