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# Bloom

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  1. bioRxiv

    Bloom learns brain-cell representations from 300,000 cells, spanning RNA and chromatin accessibility at 91%–94% subclass accuracy

    The Allen Institute for Brain Science and AWS have released Bloom, a single-cell multimodal model that encodes gene expression and chromatin accessibility into one shared cell representation while training on roughly 100-fold fewer cells than comparable pretrained models. On adult mouse whole-brain data, linear classifiers on Bloom embeddings reach 91% cross-validated adjusted balanced accuracy for 315 subclasses (multiome), 94% for 310 subclasses (scRNA-seq) and 94% for 297 subclasses (snRNA-seq), although the model saw only mouse multiome data.

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