Models

14 models · showing 14
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Geneformer Geneformer is a foundational transformer model pretrained on a large-scale corpus of human single cell transcriptomes to enable context-aware…

apache-2.0
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State Embedding model checkpoints are meant to be used with the Arc State

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

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

apache-2.0
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UCE is a zero-shot foundation model for single-cell gene expression data

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

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Deep probabilistic analysis of single-cell and spatial omics data

bsd-3-clause
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State is a machine learning model that predicts cellular perturbation response across diverse contexts

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

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

bsd-3-clause
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Single cell perturbation prediction

gpl-3.0
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Cell2Sentence-Scale (C2S-Scale) model from the van Dijk lab (Yale) and Google, fine-tuned from Gemma 2 2B.

cc-by-4.0
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Cell2Sentence-Scale (C2S-Scale) model from the van Dijk lab (Yale) and Google, fine-tuned from Gemma 2 27B.

cc-by-4.0
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rbio1 is a 3B biology reasoning model from the Chan Zuckerberg Initiative, post-trained from Qwen2.5-3B-Instruct by reinforcement learning (GRPO) with…

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