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Universal Cell Embeddings: A Foundation Model for Cell Biology | bioRxiv

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Developing a universal representation of cells which encompasses the tremendous molecular diversity of cell types within the human body and more generally, across species, would be transformative for cell biology. Recent work using single-cell transcriptomic approaches to create molecular definitions of cell types in the form of cell atlases has provided the necessary data for such an endeavor. Here, we present the Universal Cell Embedding (UCE) foundation model. UCE was trained on a corpus of cell atlas data from human and other species in a completely self-supervised way without any data annotations. UCE offers a unified biological latent space that can represent any cell, regardless of tissue or species. This universal cell embedding captures important biological variation despite the presence of experimental noise across diverse datasets. An important aspect of UCE’s universality is that any new cell from any organism can be mapped to this embedding space with no additional data la

Universal Cell Embeddings: A Foundation Model for Cell Biology | bioRxiv Skip to main content New Results Universal Cell Embeddings: A Foundation Model for Cell Biology View ORCID Profile Yanay Rosen , View ORCID Profile Yusuf Roohani , View ORCID Profile Ayush Agarwal , Leon Samotorčan , Tabula Sapiens Consortium , View ORCID Profile Stephen R. Quake , View ORCID Profile Jure Leskovec doi: https://doi.org/10.1101/2023.11.28.568918 Yanay Rosen 1 Department of Computer Science, Stanford University , Stanford, CA, USA Find this author on Google Scholar Find this author on PubMed Search for this

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