scLong: A Billion-Parameter Foundation Model for Capturing Long-Range Gene Context in Single-Cell Transcriptomics

Abstract excerpt

Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of cellular heterogeneity by providing gene expression data at single-cell resolution, uncovering insights into rare cell populations, cell-cell interactions, and gene regulation. Foundation models pretrained on large-scale scRNA-seq datasets have shown great promise in analyzing such data, but existing approaches are often limited to modeling a s...

Topics

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• COVID-19
• Aging
• Deep Learning
• Leukocytes, Mononuclear
• Phenotype
• Single-Cell Analysis
• Single-cell and spatial transcriptomics
• Single-Cell Gene Expression Analysis

Identifiers and source

Literature Corpus work

1688647f-b007-5e86-8a5d-f68fa737e5f4

DOI

10.1101/2024.11.09.622759