420-Stack: A Context-Aware Model for Single-Cell Analysis
Researchers have developed Stack, a single-cell foundation model designed to overcome the limitations of current transcriptomic tools by utilizing cellular context to improve biological discovery. Unlike previous models that function as simple denoisers, Stack employs a transformer-based architecture that captures both inter-cellular and intra-cellular relationships across large cell sets. This framework enables in-context learning, allowing the model to predict how cell populations will respond to novel conditions through a process known as cell prompting. By training on nearly 190 million…
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