Sebastian Birk

CellBridge improves cell classification in pathology images by transferring molecular information, achieving higher accuracy on fine-grained labels.

G2T reconstructs tissue geometry from gene expression data using a generative deep learning model, outperforming existing methods on spatial reconstruction benchmarks.

SQUINT learns discrete cell and niche codes from spatial transcriptomics data using residual vector quantization, outperforming baselines in identification and cross-section integration.

TERRA is a foundation model for spatial transcriptomics that predicts tissue behavior under perturbation and identifies multi-scale biological insights across tissues.

This study creates a spatially-resolved molecular atlas of human skin and uses deep learning to identify 26 niches, revealing novel immune memory structures in inflammatory skin diseases.

MintFlow is a generative AI algorithm that predicts how tissue perturbations reprogram cell states in disease, revealing novel cell populations and therapeutic targets in three human conditions.

The paper introduces NicheCompass, a graph deep learning method for characterizing cell niches in spatial omics data, showing improved performance in identifying and analyzing niches across multiple biological contexts.