Models

Geneformer Geneformer is a foundational transformer model pretrained on a large-scale corpus of human single cell transcriptomes to enable context-aware…

State Embedding model checkpoints are meant to be used with the Arc State

Source code repository mirrored from GitHub (bowang-lab/scGPT).

Source code repository mirrored from GitHub (biomap-research/scFoundation).

UCE is a zero-shot foundation model for single-cell gene expression data

A unifying representation of single cell expression profiles that quantifies similarity between expression states and generalizes to represent new studies…

Deep probabilistic analysis of single-cell and spatial omics data

State is a machine learning model that predicts cellular perturbation response across diverse contexts

GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations

The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell level.

Single cell perturbation prediction

Cell2Sentence-Scale (C2S-Scale) model from the van Dijk lab (Yale) and Google, fine-tuned from Gemma 2 2B.

Cell2Sentence-Scale (C2S-Scale) model from the van Dijk lab (Yale) and Google, fine-tuned from Gemma 2 27B.

rbio1 is a 3B biology reasoning model from the Chan Zuckerberg Initiative, post-trained from Qwen2.5-3B-Instruct by reinforcement learning (GRPO) with…