Chan Zuckerberg Biohub

Zebrafish sequence-to-function model predicting cell-type-specific gene expression from DNA sequence across embryonic development.

Hierarchical transformer with 1.2 billion parameters that predicts personalized gene expression from diploid genomes for variant effect prediction.

Activation domain predictor scoring transcriptional activator strength from protein sequence, with a 20-model ensemble that reports uncertainty.

Single-cell transcriptomics foundation model that encodes gene regulatory network structure into self-attention through graph signal processing.

Encoder-decoder codon language model that reverse-translates a protein into species-specific coding sequences for synthetic mRNA design.

Predicts haplotype-specific 3D genome organization and Hi-C contact maps from a single long-read Fiber-seq assay, using no DNA sequence as input.

Cell type annotation from multiplexed tissue images, using a pretrained Vision Transformer ensemble that runs on new panels without fine-tuning.

Virtual staining models that translate label-free light microscopy into fluorescent-equivalent predictions of nuclei and plasma membranes.