Heidelberg University

Histopathology model predicting 102 methylation-defined CNS tumor subtypes from H&E whole-slide images, with calibrated per-case confidence scores.

Vision-language encoders for chest CT that align 3D volumes with radiology reports using contrastive, report-generation, and masked-image objectives.

De novo protein backbone design conditioned on a target per-residue flexibility profile, with SE(3)-equivariant flow matching and MD validation.

Bidirectional DNA foundation model with a Mamba-attention-mixture-of-experts design, reading 1 million base pairs at single-nucleotide resolution.

Protein conformational ensemble generator conditioned on backbone geometry alone, sampling MD-like dynamics without MSAs or a folding model.

Base-pair resolution sequence-to-activity CNN predicting ATAC-seq Tn5 insertion profiles and accessibility across 90 mouse immune cell types.

Receptor activity inference from bulk or single-cell transcriptomes, reading the genes a receptor regulates instead of the receptor's own expression.

Per-residue prediction of where a receptor domain can be inserted into a protein without breaking it, for building allosteric and inducible switches.

De novo protein backbone design with geometric-algebra attention, sampling designable structures whose secondary structure matches natural proteins.

Masked-autoencoder foundation model that pre-trains a 3D Residual Encoder U-Net on roughly 39,000 brain MRIs for volumetric image segmentation.

Spot detection and quantification in 5D fluorescence microscopy. Pretrained 2D and 3D U-Nets segment foci, then Gaussian fitting measures each one.

Threshold-agnostic spot detection for 2D and 3D fluorescence microscopy, locating transcripts at subpixel accuracy via stereographic flow regression.