Article

Toward a privacy-preserving predictive foundation model of single-cell transcriptomics with federated learning and tabular modeling

2025-01-06

Abstract excerpt

The ability to pre-train on vast amounts of data to build foundation models (FMs) has achieved remarkable success in numerous domains, including natural language processing, computer vision, and, more recently, single-cell genomics—epitomized by GeneFormer, scGPT, and scFoundation. However, as single-cell FMs begin to train on increasingly large corpora, significant privacy and ethical concerns arise. Moreover, un...

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Literature Corpus work: 174a816b-0cc5-59e6-bf21-5c0531f219f6
DOI: 10.1101/2025.01.06.631427

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