Article

Learning multi-cellular representations of single-cell transcriptomics data enables characterization of patient-level disease states

2024-11-20

Abstract excerpt

Single-cell RNA-seq (scRNA-seq) has become a prominent tool for studying human biology and disease. The availability of massive scRNA-seq datasets and advanced machine learning techniques has recently driven the development of single-cell foundation models that provide informative and versatile cell representations based on expression profiles. However, to understand disease states, we need to consider entire tiss...

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Literature Corpus work: 4ba6e7a8-5272-5892-aeae-e37eeffe5eab
DOI: 10.1101/2024.11.18.624166

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